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-# TM Forum Introductory Guide
-
-# Autonomous Networks Framework
-
-IG1218F
-
-|                                                  |                                           |
-|--------------------------------------------------|-------------------------------------------|
-| <b>Maturity Level: General Availability (GA)</b> | <b>Team Approved Date: 14-Mar-2025</b>    |
-| <b>Release Status: Pre-production</b>            | <b>Approval Status: TM Forum Approved</b> |
-| <b>Version 2.0.0</b>                             | <b>IPR Mode: RAND</b>                     |
-
-# Notice
-
-Copyright © TM Forum 2025. All Rights Reserved.
-
-This document and translations of it may be copied and furnished to others, and derivative works that comment on or otherwise explain it or assist in its implementation may be prepared, copied, published, and distributed, in whole or in part, without restriction of any kind, provided that the above copyright notice and this section are included on all such copies and derivative works. However, this document itself may not be modified in any way, including by removing the copyright notice or references to TM FORUM, except as needed for the purpose of developing any document or deliverable produced by a TM FORUM Collaboration Project Team (in which case the rules applicable to copyrights, as set forth in the [TM FORUM IPR Policy](#), must be followed) or as required to translate it into languages other than English.
-
-The limited permissions granted above are perpetual and will not be revoked by TM FORUM or its successors or assigns.
-
-This document and the information contained herein is provided on an “AS IS” basis and TM FORUM DISCLAIMS ALL WARRANTIES, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF THE INFORMATION HEREIN WILL NOT INFRINGE ANY OWNERSHIP RIGHTS OR ANY IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.
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-TM FORUM takes no position regarding the validity or scope of any intellectual property or other rights that might be claimed to pertain to the implementation or use of the technology described in this TM FORUM Standards Final Deliverable or the extent to which any license under such rights might or might not be available; neither does it represent that it has made any effort to identify any such rights. Information on TM FORUM's procedures with respect to rights in any document or deliverable produced by a TM FORUM Collaboration Project Team can be found on the TM FORUM website. Copies of claims of rights made available for publication and any assurances of licenses to be made available, or the result of an attempt made to obtain a general license or permission for the use of such proprietary rights by implementers or users of this TM FORUM Standards Final Deliverable, can be obtained from the TM FORUM Team Administrator. TM FORUM makes no representation that any information or list of intellectual property rights will at any time be complete, or that any claims in such list are, in fact, Essential Claims.
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-Direct inquiries to the TM Forum office:
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-181 New Road, Suite 304  
-Parsippany, NJ 07054, USA  
-Tel No. +1 862 227 1648  
-TM Forum Web Page: [www.tmforum.org](http://www.tmforum.org)
-
-# Table of Contents
-
-|                                                                |    |
-|----------------------------------------------------------------|----|
-| Notice .....                                                   | 2  |
-| Table of Contents .....                                        | 4  |
-| Executive Summary .....                                        | 5  |
-| Introduction.....                                              | 6  |
-| 1. The Autonomous Networks Framework Overview .....            | 7  |
-| 2. Key Elements of AN Framework.....                           | 8  |
-| 2.1. Key Effectiveness Indicators .....                        | 8  |
-| 2.1.1. Indicator Framework.....                                | 8  |
-| 2.1.2. KEI Reference Set.....                                  | 10 |
-| 2.2. Autonomous Network Levels.....                            | 10 |
-| 2.2.1. Generic AN L3/L4 characteristics.....                   | 10 |
-| 2.2.2. Technical Domain-specific AN L3/L4 characteristics..... | 12 |
-| 2.2.3. AN Level Taxonomy .....                                 | 14 |
-| 2.3. AN Target Architecture .....                              | 17 |
-| 2.3.1. Conceptual Architecture .....                           | 17 |
-| 2.3.2. AN Reference Architecture.....                          | 19 |
-| 2.3.3. AI in the AN L4 Reference Architecture .....            | 19 |
-| 2.4. AN Map / High-Value Scenarios .....                       | 20 |
-| 2.4.1. High-Value Scenarios and AN Scenario Mapping .....      | 21 |
-| 2.4.2. Prioritize the Scenarios.....                           | 22 |
-| 3. Autonomous Networks Practice .....                          | 24 |
-| 4. Terms & Abbreviations Used within this Document.....        | 25 |
-| 4.1. Terminology .....                                         | 25 |
-| 5. References .....                                            | 26 |
-| 6. Administrative Appendix.....                                | 27 |
-| 6.1. Document History .....                                    | 27 |
-| 6.1.1. Version History .....                                   | 27 |
-| 6.1.2. Release History .....                                   | 27 |
-| 6.2. Acknowledgments .....                                     | 28 |
-
-# Executive Summary
-
-The AN Framework provides CSPs with a structured methodology and a comprehensive set of tools for navigating their AN transformation journey, including guidance and support for achieving the Level 4 goals of Zero-X capabilities and Self-X experiences (outlined in IG1218).
-
-This framework consists of the vision and implementation methodology, which includes foundational elements, the operational practices, and industry assessment and certification. The 4 foundational elements of AN Framework are:
-
-1. **Key Effectiveness Indicators.** KEIs help CSPs identify what benefits they could receive by upgrading their telecommunications system with more autonomy capabilities.
-2. **AN Levels.** Operators benefit from having a clear view on their expected maturity of their network so that they can focus on the important features they should prioritize to achieve a defined level of autonomy in their networks.
-3. **AN Target Architecture.** The realizations of zero-touch operations using autonomous network reference architectures aims to focus solutions on the essential principles and patterns that will improve Self-X capabilities and thereby help operators to reach L3 and L4 levels of autonomy.
-4. **Scenarios ( or "AN Map").** A mapping of high-value scenarios that helps CSPs define, prioritize, and align autonomous network capabilities with key operational and business objectives across different network lifecycle phases and service domains. It is designed to help CSPs set and decompose overall AN evolution objective from an end-to-end perspective and specify the direction and priority of *capability* development.
-
-These four elements, while relatively independent, need to be further organized to form a pragmatic how-to guide to facilitate implementation of AN. For each of these elements, pragmatic 'how-to' suggestions, as well as reference to applicable standards, are provided in this document. This document also introduces the operational practice, covering two concepts, AN strategic planning and AN Journey. The industry assessment and certification of AN is at an earlier stage of development, and will be elaborated in a future revision of this document.
-
-# Introduction
-
-This document introduces the overall framework and practice methods of AN Framework (ANF). It aims to provide a systematic method for operators from AN strategy planning to implementation, and guide operators to carry out AN work more efficiently. C-level and senior managers, should focus on the value proposition and AN level characteristics of AN Framework, control the direction of value and capability evolution of AN, understand the value brought by AN, and confirm whether AN goals are achieved. The general owner of the AN work can focus on the ANF's effectiveness indicators, evaluation standards, target architecture, and the AN map, to formulate the operator's strategic plan (ANSP), specify the overall objective and evolution path, define the key business scope of the AN, and coordinate the work division and capability evolution pace of each system. The AN implementation personnel of various technology and service domains can focus on the AN Journey, master the closed-loop implementation methods based on value scenarios, and perform iterative evolution to continuously improve the AN level.
-
-# 1. The Autonomous Networks Framework Overview
-
-The AN Framework is an out-of-the-box implementation guide and toolkit to guide CSPs' AN transformation so that they can plan and implement AN in a more efficient and systematic manner and more quickly fulfill the vision of Zero-X and Self-X.
-
-The Autonomous Network Framework (ANF) is structured into two key aspects:
-
-1. **AN Foundations** (depicted in the top half of the figure 1) – These are the core building blocks that define the vision, methodology, and essential elements needed to enable AN evolution. They include **Key Effectiveness Indicators (KEIs)**, **AN Levels**, **the AN Target Architecture**, and **the "AN Map"** or High-Value Scenarios matrix. These four elements provide the structure for AN development.
-2. **AN Practices** (depicted in the bottom half of the figure 1) – These focus on putting AN into action, guiding CSPs through the implementation and operationalization of AN. AN practices consist of two key activities:
-  - **AN Strategic Planning:** A structured approach for CSPs to define and guide their AN evolution. It includes corporate-level AN strategies, executive commitments, and guidance on implementing the four foundational elements of ANF. Additionally, it outlines industry contributions and technological innovation directions.
-  - **The AN Journey:** An **iterative process** where operators execute strategies, measure progress, and refine their approach to achieve AN objectives.
-
-By leveraging the AN Foundations within operator AN Practices, CSPs can systematically evolve their networks toward higher levels of autonomy, ensuring both strategic alignment and practical execution.
-
-![Autonomous Networks Framework diagram showing the relationship between Basic Propositions, Operations Practices, and the overall Vision of Zero-X/Self-X.](1c953f32bd34345dfd68fddf8a3736d6_img.jpg)
-
-The diagram illustrates the Autonomous Networks Framework (ANF) structure. At the top, the **Vision: Zero-X/Self-X** is stated. Below this, the framework is divided into two main horizontal sections: **Basic Propositions** (top) and **Operations Practices** (bottom).
-
-**Basic Propositions** are organized into four columns, each representing a key element:
-
-- Benefit:** Value propositions (Business value + social value) leading to **1. KEIs** (Indicator framework + reference indicator set).
-- Evolution:** Level characteristics (Generic + Domain-specific) leading to **2. AN level** (ANL standards + assessment methods and tools).
-- Cooperation:** Architecture principles (Single-domain autonomy/cross-domain collaboration, intent-driven, full-stack AI, closed-loop automation) leading to **3. Target architecture** (Business architecture + technical architecture).
-- Scope:** Processes and methods (Scenario definition principles + priority model) leading to **4. AN map** (High-value scenario framework + scenario/capability set).
-
-**Operations Practices** are divided into two main areas:
-
-- ANSP (Autonomous Network Strategic Planning):** Includes Inputs (Business strategies, High-level requirements, Industry standards, Cutting-edge technologies, Third-party assessment report), Key actions (Strategy intent, Business planning, Strategy oversight, Strategy breakdown), and Outputs (AN strategies, Management commitments, AN blueprint (four elements), Industry strategies and contributions, Technological innovation).
-- AN Journey:** Includes Assessment (Effectiveness/level assessment and objective formulation), Implementation (Development and deployment of three-layer capabilities, and pilot verification/large-scale promotion), Gap analysis (Process walk-through, gap identification, and items of action), and Solution design (Application architecture design, three-layer system specifications/APIs, and key technologies).
-
-A vertical red bar on the right side of the diagram represents **Industry assessment and certification**, which includes **Service experience**, **Industry assessment and certification**, and **Network capability**.
-
-At the bottom, the **Organization** section includes **Organizational assurance** (decision-making, planning, and special project teams) and **Organizational transformation** (organization, process, people, etc.).
-
-Autonomous Networks Framework diagram showing the relationship between Basic Propositions, Operations Practices, and the overall Vision of Zero-X/Self-X.
-
-Figure 1. Autonomous Networks Framework
-
-The AN Framework includes all four key elements, operational practices, training, assessment, and certification.
-
-# 2. Key Elements of AN Framework
-
-## 2.1. Key Effectiveness Indicators
-
-When an enterprise plans to undertake a strategy or investment, it must align its values and goals within the organization and measure the return on investment. Central to this process is the definition and measurement of key indicators.
-
-IG1252 [3] defines an evaluation methodology for Autonomous Networks Levels (AN Level). AN Levels gauge the level of autonomy capability in a given operational workflow or autonomous domain. However, AN Levels do not adequately reflect the overall impact or value of an autonomous network. Hence, there is a need to establish Key Effectiveness Indicators (KEIs) to help CSPs in determining the benefits of enhancing their telecommunications system with greater autonomy capabilities.
-
-The value of these indicators lies in two aspects:
-
-1. visualizing and quantifying the effectiveness and benefits of AN evolution,
-2. and aligning the development of autonomous capabilities with the enterprise strategy and service development trend.
-
-Effectiveness indicators and AN levels are the two key AN evaluation factors that jointly facilitate the fulfillment of the Autonomous Network vision. KEIs can be used in the following three situations:
-
-1. Formulating *improvement objectives* for AN based on KEIs. For example, if the service delivery target at L4 is measured in minutes, the target baseline can be set based on an opco's O&M status, experience of benchmark CSPs and annual investment budget. Note that the baseline value is not equivalent to a characteristic of L4.
-2. Guiding *capability development* by associating KEIs with operation capabilities and converting and breaking down capability requirements for example, the time needed for optical transport network private line service delivery can be broken down into various key capability indicators, such as the time needed for CPE deployment and solution design. These capability metrics can be mapped to specific functional requirements for support systems, operations and maintenance (O&M) centers, and network elements.
-3. Verifying the *effectiveness of operation capability* development based on KEIs to provide inputs for the next AN Journey – the inputs include adjustments to the rationality of objectives, investment plan changes and optimized development directions.
-
-### 2.1.1. Indicator Framework
-
-Traditional KPIs are typically established in response to O&M challenges or identified weaknesses. For instance, when there are numerous customer complaints, indicators like the complaint rate are introduced to guide teams in enhancing product quality and service processes while reducing customer grievances. However, this approach primarily addresses isolated issues and lacks comprehensive planning and target guidance. It falls short of systematically steering organizational and platform capability development. In light of this, drawing from the balanced scorecard theory, the existing **TM Forum Metrics** framework (GB935 [10] / GB988 [11], etc.), and insights gained from operator autonomous network KEI design practices, we propose
-
-an autonomous network KEI framework. The design and decomposition methodology for this framework are illustrated in the following diagram, Figure 2.
-
-![Diagram of the Autonomous Networks and Operation Indicators Framework showing the hierarchy from KBI to KCI.](b3baf3a29b67c7425d2562ddbc52f0cc_img.jpg)
-
-**Autonomous Networks and Operation Indicators Framework**
-
-The diagram illustrates the Autonomous Networks and Operation Indicators Framework, structured into three levels: KBI (Key Business Indicators), KEI (Key Effectiveness Indicators), and KCI (Key Capability Indicators).
-
-- KBI Level:** Contains five primary indicators:
-  - Reduced O&M Costs
-  - Number of Employee Who Have Transitioned
-  - Revenue from Operations
-  - Revenue from Open Capabilities
-  - Number of major faults
-- KEI Level:** Decomposes the KBI indicators into specific metrics:
-  - Reduced O&M Costs:** Fairness cooperation, Incentive cooperation, Safety Cooperation, Efficient cooperation, Cooperation Energy Saving Reward, Power Usage Effectiveness, Device Power-saving Ratio, Resource Deployment Time, Mean Time to Recovery, Complaint Resolution Time.
-  - Number of Employee Who Have Transitioned:** Service Delivery Time, Mean Time to Recovery, Complaint Resolution Time.
-  - Revenue from Operations:** Service Delivery On-time Ratio, First Call Resolution Ratio, Complaint Resolution On-time Ratio, Quality Complaint Ratio, SLA Compliance Ratio, Service Availability Ratio, Service Interruption Time, Resource Requirement Fulfillment Ratio, Reasonable resource utilization, Service Delivery Time, Complaint Resolution Time, Mean Time to Recovery.
-  - Revenue from Open Capabilities:** Time To Market, Naas APIs Count.
-  - Number of major faults:** Fault Handling On-time Ratio, Proactive Maintenance Ticket Ratio, Mean Time to Recovery, ....
-- KCI Level:** Contains two primary indicators:
-  - Automation Ratio
-  - Intelligent Ratio
-
-Diagram of the Autonomous Networks and Operation Indicators Framework showing the hierarchy from KBI to KCI.
-
-**Figure 2. Indicator Framework**
-
-The key features of this indicator framework are outlined below:
-
-1. **Value-Centric Approach:** KEIs are deliberately designed from a 'top-down' perspective, aligning with the four primary value propositions of the autonomous network. Each KEI is directly or indirectly linked to enhancing one or more of these value propositions. A corresponding set of effectiveness indicators is established for each recognized value proposition, facilitating effective measurement of the value delivered.
-2. **Multi-Level Hierarchical Structure:** The KEIs are structured hierarchically, systematically breaking down the measurement levels based on the identified value propositions. This hierarchical structure forms a causal indicator tree. The KPIs reflect the main AN value propositions, offering a holistic view of AN's impact at both the company and industry levels. Simultaneously, it provides guidance on achieving effectiveness and establishes internal appraisal requirements. Within each domain, detailed KPI rules can be formulated, and specific targets can be set based on the domain's unique KPIs and specialized areas of business. Furthermore, **KCIs** can be further subdivided, driven by an analysis of process activities and identified capability gaps during the AN journey within valuable scenarios. This sub-level decomposition guides the development of system capabilities more effectively.
-
-The distinction between KPIs and KCIs lies in their respective purposes. KPIs are business-oriented KEIs that focus on end-to-end outcomes, while KCIs serve as capability measures aimed at bolstering the attainment of Key Effectiveness Indicators (KEIs) by addressing specific process activity weaknesses. **In essence, KEIs measure the achievement of business objectives, while KCIs gauge key capabilities.** As technology and capabilities evolve, the essential KCIs within a process may undergo changes, whereas KEIs tend to remain relatively stable. For instance, consider a troubleshooting scenario within a domain where the KEI is the average troubleshooting duration. At
-
-present, accurately identifying faults poses a challenge. Therefore, a suitable KCI can be defined as 'Fault Identification Accuracy.' As fault identification capabilities improve, the key weakness may shift to fault diagnosis. Accordingly, KCIs can be redefined as 'Automatic Fault Diagnosis Rate' and 'Fault Diagnosis Accuracy Rate' to address this evolving capability requirement.
-
-3. **Consider both benefit and efficiency:** When defining KEIs, it is important to consider not only efficiency indicators like automation rates but also business benefit indicators such as time consumption and quality. By incorporating both benefit and efficiency aspects, a more comprehensive measurement system for KEIs can be developed. For example, in troubleshooting scenarios, it's essential to define not just the efficiency indicator of troubleshooting automation rates but also the benefit indicator of average troubleshooting duration.
-
-### 2.1.2. KEI Reference Set
-
-For details about the reference set of effectiveness indicators and the definition of specific indicators, see IG1256 Autonomous Network Effectiveness Indicators [4].
-
-The following is an example:
-
-| Indicator name                     | Time to Market                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             | Abbreviation | TTM |
-|------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------|-----|
-|                                    |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            | Unit         | Day |
-| <b>Definition of the indicator</b> | Measure the time taken for new services or products from the initial concept stage to market launch.                                                                                                                                                                                                                                                                                                                                                                                                                       |              |     |
-| <b>Indicator Description</b>       | This indicator reflects the ability of enterprises to launch new services or products. The shorter the time to market, the quicker a return on investment can be realized. AN capability such as self-orchestration and self-loading can quickly support the design, development, verification, and release of new services and products. The intent-based interface simplifies inter-system interconnection and shortens the integration time. All these AN capabilities can effectively shorten the product launch time. |              |     |
-| <b>Calculation formula</b>         | <p>TTM = Total time from concept to launch of all new services or products ÷ Number of new services or products</p> <p>Go-to-market (or go-to-shelf) refers to the formal sale of a product in the market and users can already buy the product.</p>                                                                                                                                                                                                                                                                       |              |     |
-
-Table 1. KEI Reference Set Example
-
-## 2.2. Autonomous Network Levels
-
-### 2.2.1. Generic AN L3/L4 characteristics
-
-There is now industry consensus that AN Levels are defined based on cognitive closed-loop theory and the degrees of a human-machine division of labor. An increasing number of AN practitioners want to take an approach that is straightforward in that it defines AN Level characteristics in terms of business or service value. The IG1326 Autonomous Networks: Empowering digital transformation – evolving from Level 2/3 towards Level 4 [9] has summarized general L4 characteristics and the key points of L3-to-L4 evolution from business and capability perspectives as shown in Table 2 below. Domain-specific L4 characteristics can be defined based on the guiding principles of the general L4 characteristics shown in the table.
-
-| Generic L3/L4 Characteristic |                    |                                        |                                                 |                                                                                                                                                                                                                                                                                                                                  |
-|------------------------------|--------------------|----------------------------------------|-------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| Perspective                  | Dimension          | L3 Characteristic                      | L4 Characteristic                               | Description                                                                                                                                                                                                                                                                                                                      |
-| Customer                     | Zero-wait          | Automated service provisioning         | Automated service delivery                      | <p><b>L3:</b> Services are configured automatically in the provisioning phase. Other phases involve manual operations.</p> <p><b>L4:</b> Resource surveys are no longer required. Self-acceptance is supported. E2E automation is implemented from receiving delivery tickets by network personnel to returning the tickets.</p> |
-|                              | Zero-trouble       | Experience awareness and visualization | Experience evaluation and assurance             | <p><b>L3:</b> User experience is visualized, and complaints are diagnosed automatically.</p> <p><b>L4:</b> Experience can be evaluated and guaranteed, and warnings can be generated for potential complaints.</p>                                                                                                               |
-|                              | Zero-touch         | Visualization                          | Interaction                                     | <p><b>L3:</b> Customer service provisioning progress and SLA are visualized.</p> <p><b>L4:</b> Proactive recommendation and intelligent response are supported.</p>                                                                                                                                                              |
-| Network                      | Self-configuration | Automated configuration delivery       | Pre-event simulation<br>Post-event verification | <p><b>L3:</b> Configurations are automatically delivered and manually reviewed.</p>                                                                                                                                                                                                                                              |
-
-| Generic L3/L4 Characteristic |                 |                                         |                                            |                                                                                                                                                                                                                                                        |
-|------------------------------|-----------------|-----------------------------------------|--------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-|                              |                 |                                         |                                            | <b>L4:</b> Configurations are automatically generated and simulated online, eliminating the need for manual review.                                                                                                                                    |
-|                              | Self-healing    | Precise fault diagnosis                 | Potential risk prediction and prevention   | <b>L3:</b> Faults can be accurately demarcated and located.<br><br><b>L4:</b> Potential risks can be predicted and prevented, and faults can be automatically rectified.                                                                               |
-|                              | Self-optimizing | Single-objective exclusive optimization | Multi-objective collaborative optimization | <b>L3:</b> Optimization can be performed exclusively for a single objective – for example, wireless network performance.<br><br><b>L4:</b> Optimization can be performed for multiple objectives – for example, user experience and energy efficiency. |
-
-Table 2. Evolving from L3 to L4
-
-### 2.2.2. Technical Domain-specific AN L3/L4 characteristics
-
-Based on the generic AN L3/L4 characteristics, the technical domain AN L3/L4 characteristics are summarized as follows:
-
-| Wireless Network L3/L4 Characteristic |                                         |                                                             |
-|---------------------------------------|-----------------------------------------|-------------------------------------------------------------|
-| Dimension                             | L3 Characteristic                       | L4 Characteristic                                           |
-| Intelligent Sensing                   | Non-real-time sensing                   | Real-time intelligent sensing                               |
-| Intelligent and Simplified O&M        | Machine-assisted O&M, precise diagnosis | Machine-guided O&M, intent driven prediction and prevention |
-| Intelligent Network Optimization      | Single-objective optimization           | Intent driven multi-Objective optimization                  |
-| Intelligent Service Operation         | Best Effort Experience                  | Intent driven deterministic Experience                      |
-
-Table 3. Wireless Network Evolving from L3 to L4
-
-| Core Network L3/L4 Characteristic |                                                                           |                                                                                                |
-|-----------------------------------|---------------------------------------------------------------------------|------------------------------------------------------------------------------------------------|
-| Dimension                         | L3 Characteristic                                                         | L4 Characteristic                                                                              |
-| Intelligent O&M                   | Rule-based automation in some scenarios                                   | Automation in most scenarios based on AI technologies                                          |
-| Agile Delivery                    | Rule-based provisioning, change, verification and testing, some scenarios | AI-based check, AI and digital twin-based verification and testing, cover almost all scenarios |
-| High Reliability                  | Fast recovery from multipoint faults                                      | Proactive prevention, intelligent risk prevention and control                                  |
-
-Table 4. Core Network Evolving from L3 to L4
-
-| IP Network L3/L4 Characteristic  |                                                                    |                                                                                              |
-|----------------------------------|--------------------------------------------------------------------|----------------------------------------------------------------------------------------------|
-| Dimension                        | L3 Characteristic                                                  | L4 Characteristic                                                                            |
-| Agile Service Routing            | Work order-driven, day-level provisioning                          | Application driven, minute-Level intent provisioning                                         |
-| Premium Deterministic Experience | Optimal latency and self-tuning                                    | Deterministic experience, guaranteed latency and availability, and proactive self-tuning     |
-| No Config Error                  | Resource-based autoconfiguration                                   | Service intent-based configuration with pre-check and post-check validation                  |
-| Efficiency Fault-removing        | Fault locating and isolation with on-path flow-based OAM mechanism | Intelligent fault/potential risk identification and self-demarcation and locating in minutes |
-
-Table 5. IP Network Evolving from L3 to L4
-
-| Access Network L3/L4 Characteristic |                                                                                                  |                                                                                                               |
-|-------------------------------------|--------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------|
-| Dimension                           | L3 Characteristic                                                                                | L4 Characteristic                                                                                             |
-| Online Service Deployment           | Work order-driven one-stop planning, construction, and verification, enabling the system in days | Application-driven, application and flow level deterministic experience slicing, enabling services in seconds |
-| Customer Complaint Handling         | Broadband experience visualization                                                               | Experience evaluation and self-repair                                                                         |
-| Quality Optimization                | Proactive identification of experience faults and hour-level fault locating and demarcation      | Proactive identification and demarcation, and self-optimization                                               |
-
-Table 6. Access Network Evolving from L3 to L4
-
-| Transmission Network L3/L4 Characteristic |                                                            |                                                                                                          |
-|-------------------------------------------|------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|
-| Dimension                                 | L3 Characteristic                                          | L4 Characteristic                                                                                        |
-| Assorted Service Automation               | Work order-driven, day-level provisioning                  | Compute/Cloud application driven, online wavelength planning, minute-level provisioning                  |
-| Ultimate SLA Guaranteed                   | Optimal latency, automatic SLA configuration               | Deterministic bandwidth + latency + availability commitment, interactive SLA self-tuning                 |
-| Time-saving Ticket Journey                | Static rule filtering, hour-level demarcation and locating | Intelligent fault/potential risk identification and interactive self-demarcation and locating in minutes |
-
-Table 7. Transmission Network Evolving from L3 to L4
-
-### 2.2.3. AN Level Taxonomy
-
-The AN Level Taxonomy classifies the degree or *level* of automation and intelligence in CSP networks, ranging from basic automation to full autonomy. This standard can be used to evaluate the levels of autonomy, identify weaknesses in autonomous capabilities, analyze gaps between the status quo and objectives, and guide CSPs to systematically plan and deploy autonomous capabilities.
-
-The technical work of AN Level evaluation methodology is published in IG1252 Autonomous Network Levels Evaluation Methodology [3], which describes the AN Level evaluation approach and operation flows, tasks evaluation criteria, scoring method, etc. The table below shows the levels in more detail, with additional explanation of the levels following.
-
-| Autonomous Levels   | L0:<br>Manual Operation & Maintenance | L1:<br>Assisted Operation & Maintenance | L2:<br>Partial Autonomous Networks | L3:<br>Conditional Autonomous Networks | L4:<br>Highly Autonomous Networks | L5:<br>Fully Autonomous Networks |
-|---------------------|---------------------------------------|-----------------------------------------|------------------------------------|----------------------------------------|-----------------------------------|----------------------------------|
-| Execution           | P                                     | P/S                                     | S                                  | S                                      | S                                 | S                                |
-| Awareness           | P                                     | P/S                                     | P/S                                | S                                      | S                                 | S                                |
-| Analysis            | P                                     | P                                       | P/S                                | P/S                                    | S                                 | S                                |
-| Decision            | P                                     | P                                       | P                                  | P/S                                    | S                                 | S                                |
-| Intent / Experience | P                                     | P                                       | P                                  | P                                      | P/S                               | S                                |
-| Applicability       | N/A                                   | Selected Scenarios                      |                                    |                                        |                                   | All Scenarios                    |
-
-P
-
-People (manual)
-
-S
-
-System (autonomous)
-
-Table 8. Autonomous Network Level Taxonomy
-
-**Level 0 – Manual management:** the system delivers assisted monitoring capabilities, which means all dynamic tasks must be executed manually.
-
-**Level 1 – Assisted management:** the system executes a certain repetitive sub-task based on pre-configuration to increase execution efficiency.
-
-**Level 2 – Partially Autonomous Networks:** the system enables partial automatic O&M for certain units based on pre-defined rules or policies under certain external environments.
-
-**Level 3 – Conditionally Autonomous Networks:** building on L2 capabilities, the system with awareness can sense real-time environmental changes, and in certain network domains, optimize and adjust itself to the external environment.
-
-**Level 4 – Highly Autonomous Networks:** building on L3 capabilities, the system enables, in a more complicated cross-domain environment, analysis and decision-making based on predictive or active closed-loop management of service and customer experience-driven networks.
-
-**Level 5 – Fully Autonomous Networks:** this level is the goal for telecom network evolution. The system possesses closed-loop automation capabilities across multiple services, multiple domains and the entire lifecycle, achieving Autonomous Networks.
-
-The AN Level can be applied to generic domain or to a specific network domain (i.e domain-specific). On the one hand, we need to unify the concepts, principles and methods so that the AN Levels of different networks and services can be compared horizontally. On the other hand, the specific network and service characteristics of a given domain must be considered to better guide the AN capability planning and construction of different networks and services.
-
-The IG1305 Autonomous Networks: Empowering digital transformation – from strategy to implementation [8] further describes the generic AN Level and domain-specific AN Level and the relationship between them.
-
-![Diagram illustrating the relationship between Generic ANL and Domain-specific ANL. The top box, 'Generic ANL', describes general concepts for all domains and services. An upward arrow labeled 'Summary' points to the bottom box, 'Domain-specific ANL', which details standards for specific domains and services. The bottom box is divided into 'Domains' (Wireless, Core, Access, Transport, IP, More) and 'Services' (Individual consumer, Home, Public sector and enterprise, More).](70de8885bd7de15723aaad5eb5c5febf_img.jpg)
-
-**Generic ANL**
-
-General ANL concepts, principles, and methods for **all domains and services**
-
-↑ Summary      ↓ Refinement
-
-**Domain-specific ANL**
-
-Detailed standards defined **based on the generic ANL** to guide the evolution of autonomous capabilities in each domain or service
-
-| <b>Domains</b> |      |        | <b>Services</b>              |      |
-|----------------|------|--------|------------------------------|------|
-| Wireless       | Core | Access | Individual consumer          | Home |
-| Transport      | IP   | More   | Public sector and enterprise | More |
-
-Diagram illustrating the relationship between Generic ANL and Domain-specific ANL. The top box, 'Generic ANL', describes general concepts for all domains and services. An upward arrow labeled 'Summary' points to the bottom box, 'Domain-specific ANL', which details standards for specific domains and services. The bottom box is divided into 'Domains' (Wireless, Core, Access, Transport, IP, More) and 'Services' (Individual consumer, Home, Public sector and enterprise, More).
-
-**Figure 3. Generic AN Level Characteristics and Domain-specific AN Level Characteristics**
-
-- **Generic AN Level** is applicable to all domains and services. It focuses on the AN Level concepts, principles, methods, and O&M task baselines, offering basic categories for the usage and instantiation of domain-specific AN Level. The core value of generic AN Level lies in ensuring consistent dimensions, granularities, and terms of O&M tasks between different domains or services to support horizontal comparison and analysis of the AN Level evaluation result. The Generic AN Level definition and evaluation method are described in TM Forum IG1252 [3].
-- **Domain-specific AN Level** is applicable to a specific domain or service. It defines the detailed rules for the domain or service based on the generic AN Level, including the assessment rules of L1 to L5 and baseline scenarios. Domain-specific AN Level can be used to evaluate the AN Level of the domain or service and guide the evolution of autonomous capabilities in the domain or service. For templates and examples of domain-specific AN Level, see Figure 4. Domain-specific AN Level and evaluation method are defined by respective SDOs, e.g. 3GPP network and service AN Level is defined in 3GPP. TS28.100 [7].
-
-Image: Figure 4: Domain-specific AN Level and function map. The diagram shows a table with columns for Operation flow, Sub-operation flow, Operation task, Evaluation Criteria (XX Domain), Selected Scenario (Sub-scenario1, Sub-scenario2), and Function Map (BSS, OSS, Network Layer). The table is divided into two main sections: 'Domain-specific ANL' and 'Function breakdown'.
-
-| Domain-specific ANL |                    |                        |                                 |                   | Function breakdown |              |            |               |
-|---------------------|--------------------|------------------------|---------------------------------|-------------------|--------------------|--------------|------------|---------------|
-| Operation flow      | Sub-operation flow | Operation task         | Evaluation Criteria (XX Domain) | Selected Scenario |                    | Function Map |            |               |
-|                     |                    |                        |                                 | Sub-scenario1     | Sub-scenario2      | BSS          | OSS        | Network Layer |
-| Maintenance         | Fault management   | Fault identification   | L1:<br>L2:<br>L3:<br>L4:        | 2                 | 3                  | N/A          | L3:<br>L4: | L3:<br>L4:    |
-|                     |                    | Demarcation & Location | ... ..                          |                   |                    | ... ..       | ... ..     | ... ..        |
-
-**Figure 4. Domain-specific AN Level and function map**
-
-To systematically strategize and cultivate autonomous capabilities while providing clearer guidance to Operators in reaching Levels 3 (L3) and 4 (L4), we deconstruct functional requirements within the BSS, OSS, and network layers (comprising NMSs and NEs). This deconstruction is based on domain-specific Autonomous Network Level criteria and the key AN architecture principles, namely single-domain autonomy and cross-domain collaboration. The resulting functional requirements collectively compose what we refer to as the 'function map.' The domain-specific AN Level defines the objectives of L3 and L4, whereas the function map illustrates the means to achieve these levels. Figure 4 provides an illustrative example of domain-specific AN Level, with a specific focus on the function map related to the domain-specific AN Level.
-
-CSPs need to determine whether they require a comprehensive and systematic evaluation or if a preliminary, more cursory assessment suffices. Systematic evaluation involves a comprehensive assessment of the autonomy level within a specific domain based on domain-specific AN Level criteria. It entails comparing the existing state to predefined objectives and pinpointing any identified weaknesses and gaps. The function map serves as a valuable tool for strategizing and evolving system functions aimed at enhancing weaknesses and closing gaps. For a rapid and preliminary assessment, a questionnaire is devised, based on the domain-specific AN Level. This questionnaire enables participants to swiftly grasp the evaluation process and provide a rough estimation of a Communication Service Provider's (CSP) autonomy level.
-
-## 2.3. AN Target Architecture
-
-The complete AN target architecture includes the architecture vision, AN framework, architecture principles and technical reference architecture comprehensively defined by TM Forum, ETSI and domain-specific SDOs.
-
-To define the Autonomous Network (AN) target architecture, CSPs can follow this structured process:
-
-1. **Establish the architectural vision and principles** by drawing insights from corporate strategic directives, business strategies, technical prerequisites, architecture requirements, AN standards, and prevailing industry technology trends.
-2. **Articulate a reference architecture** that aligns with corporate strategic goals, drawing from AN's functional reference architecture and existing architectural capabilities. This involves conducting process walk-throughs, identifying value streams, and summarizing business capability requirements. Throughout this phase, CSPs should identify significant architecture gaps and provide essential improvement recommendations. Operators should particularly emphasize two key aspects: defining an efficient architectural division of labor to expedite service innovation and reduce overall costs, and implementing formalized data and models to support hierarchical AI integration and closed-loop automation.
-3. **Put architectural principles into practice** in alignment with corporate strategic objectives for specific business scenarios. Enhance business capabilities based on assessments of AN Level and effectiveness.
-4. **Continuously refine the target architecture** in an iterative manner, drawing insights from issues encountered during implementation.
-
-### 2.3.1. Conceptual Architecture
-
-The TM Forum framework that members are building identifies three layers and four closed loops to deliver Autonomous Networks (see Figure 5). The three layers are common capabilities of operations that can be utilized to support all scenarios and business needs:
-
-1. **Resource Operations layer** – provides automation of network resources and capabilities in each autonomous domain level
-2. **Service Operations layer** – provides the capabilities for IT services and network planning, design, rollout, provisioning, assurance and optimization of operations across multiple autonomous domains
-3. **Business Operations layer** – provides the capabilities for customer, ecosystem and partner business enabling and operations for AN services
-
-![Figure 5: Conceptual Architecture. This diagram illustrates the four closed loops of interaction across four layers: Users, Commercialization, Production, and Autonomous domains. The layers are separated by dashed lines. The Users layer includes 'Operations Efficiency' (Personalized services, Automated O&M, Real-time experience) and 'Business Growth' (Smart City, Smart home, Smart manufacturing). The Commercialization layer contains 'Business operations'. The Production layer contains 'Services operations'. The Autonomous domains (X and Y) contain 'Resource operations' (PE and VE). Four red loops are shown: 1. User closed-loop (spanning all layers), 2. Business closed loop (between Commercialization and Production), 3. Service closed loop (between Production and Autonomous domains), and 4. Resource closed loop (within Autonomous domains). Arrows indicate 'Business intent', 'Service intent', and 'Resource intent' flows between layers.](dfe556fea00682b09a59427aaf72051c_img.jpg)
-
-Figure 5: Conceptual Architecture. This diagram illustrates the four closed loops of interaction across four layers: Users, Commercialization, Production, and Autonomous domains. The layers are separated by dashed lines. The Users layer includes 'Operations Efficiency' (Personalized services, Automated O&M, Real-time experience) and 'Business Growth' (Smart City, Smart home, Smart manufacturing). The Commercialization layer contains 'Business operations'. The Production layer contains 'Services operations'. The Autonomous domains (X and Y) contain 'Resource operations' (PE and VE). Four red loops are shown: 1. User closed-loop (spanning all layers), 2. Business closed loop (between Commercialization and Production), 3. Service closed loop (between Production and Autonomous domains), and 4. Resource closed loop (within Autonomous domains). Arrows indicate 'Business intent', 'Service intent', and 'Resource intent' flows between layers.
-
-**Figure 5. Conceptual Architecture**
-
-The four closed loops identified to fulfill the full lifecycle of the inter-layer interaction are:
-
-1. **User closed loop** – the interaction across three layers and three closed loops to support fulfillment of the user's service
-2. **Business closed loop** – the interaction between business and service operations may trigger related service and resource closed loops in its fulfillment
-3. **Service closed loop** – the interaction between service and network resource operations may trigger related resource closed loops in its fulfillment
-4. **Resource closed loop** – the interaction of network resource operations is in the granularity of autonomous domains
-
-Autonomous Networks are characterized by autonomous domains and automated intelligent business, service and resource operations for the closed-loop of digital business, which offer the best-possible user experience, full lifecycle operations automation/autonomy and maximum resource utilization.
-
-The basic principles of the operations of autonomous domains are:
-
-- **Single Domain Autonomy** – each autonomous domain runs in self-operating mode per business objective and hides the details of domain implementation, operations and the functions of the domain elements from the users of the autonomous domains by using an abstraction layer of service APIs.
-- **Cross Domain Collaboration** – multiple instances of autonomous domains can be collaborated on by upper layer service operations using the intent-driven interaction to fulfill the lifecycle of network/ICT services.
-
-### 2.3.2. AN Reference Architecture
-
-Autonomous networks aim to make processes more efficient and intelligent to better serve human needs and enhance overall decision-making. Achieving end-to-end autonomy requires collaboration across the industry. To handle the complexity of various services and technologies, TM Forum and other organizations have created standards and workflows for seamless communication between different layers. TM Forum's autonomous network reference architecture focuses on essential principles and patterns to improve Self-X capabilities, helping operators reach Levels 3 and 4 of autonomy ( IG1251 Autonomous Networks – Reference Architecture [2], Figure 6.)
-
-![Figure 6: AN Reference Architecture (showing detailed ADs at all layers). The diagram illustrates a multi-layered architecture. At the top is 'AN Consumers (External Ecosystem - B2B, B2C, etc.)'. Below this are three layers: 'Business Operations' (F1), 'Service Operations' (F2), and 'Resource Operations' (F3). Each layer contains 'Domain Intelligence' and 'Domain Control Loop Management' (Awareness, Analysis, Decision, Execution). The 'Resource Operations' layer is further divided into 'Autonomous Domain' and 'Autonomous Domain (Detailed)'. A vertical bar on the right represents 'Knowledge and Intelligence', including 'Application Catalog', 'Model Training', 'Knowledge Base', and 'Data Services'. The diagram also shows 'Intent Management' and 'Domain Intelligence' components across the layers. A legend at the bottom right explains the notation: '1..N Autonomous Domains (AD)', '--- Only ADs at resource layer shown for simplicity', and '* SI: Site Intelligence'.](10781f43062bf3e9601a1e086710556c_img.jpg)
-
-Figure 6: AN Reference Architecture (showing detailed ADs at all layers). The diagram illustrates a multi-layered architecture. At the top is 'AN Consumers (External Ecosystem - B2B, B2C, etc.)'. Below this are three layers: 'Business Operations' (F1), 'Service Operations' (F2), and 'Resource Operations' (F3). Each layer contains 'Domain Intelligence' and 'Domain Control Loop Management' (Awareness, Analysis, Decision, Execution). The 'Resource Operations' layer is further divided into 'Autonomous Domain' and 'Autonomous Domain (Detailed)'. A vertical bar on the right represents 'Knowledge and Intelligence', including 'Application Catalog', 'Model Training', 'Knowledge Base', and 'Data Services'. The diagram also shows 'Intent Management' and 'Domain Intelligence' components across the layers. A legend at the bottom right explains the notation: '1..N Autonomous Domains (AD)', '--- Only ADs at resource layer shown for simplicity', and '\* SI: Site Intelligence'.
-
-Figure 6. AN Reference Architecture (showing detailed ADs at all layers)
-
-TM Forum IG1251A [5] also presents the details of how technology specific SDOs coordinate with each other on autonomous network architecture. The realizations build on the core concepts of AN (defining closed loops, using intent-driven interfaces) enables the autonomy at various management scopes. Multiple realizations of different management scopes are coordinated with each other and form an end-to-end AN solution to achieve the overall AN vision.
-
-- Domain management: e.g., 3GPP SA5, ETSI F5G, IETF.
-- Cross-domain management: e.g., TM Forum AN, ETSI ZSM.
-
-### 2.3.3. AI in the AN L4 Reference Architecture
-
-At Autonomous Networks Level 4, AI and **Generative AI (GenAI)** are widely integrated into AN's three-layer architecture. Two types of AI-driven agents enhance autonomy at each layer: **copilots** designed for operational roles and **scenario-based agents** tailored for specific operational needs.
-
-- **Business/Service operations:** Agents are developed for users, businesses, and service operations to achieve an E2E autonomous closed loop. AI/GenAI on which the agents depend can be implemented in either of the following modes:
-  - Model inference integrated to the agents
-  - Model training/inference centrally provided by the cloud AI center
-
-- **Resource operations:** Agents integrating AI/GenAI model inference collaborate with intelligent NEs to implement a closed loop of single-domain network autonomy.
-- **Network Elements (NEs):** Built-in AI models offer local inference, high-precision awareness, and control capabilities.
-
-![Figure 7: Full-stack AI/GenAI in the AN architecture. This diagram illustrates a three-layer architecture across four domains: Users, Commercialization, Production, and Autonomous domains. The Users layer includes 'Operations Efficiency' (Personalized Services, Automated O&M, Real time Experience) and 'Business Growth' (Smart City, Smart Home, Intelligent Manufacturing). The Commercialization layer shows 'Business operations' with a 'User closed loop' (1) and 'Business intent' flow. The Production layer shows 'Services operations' with a 'Business closed loop' (2) and 'Service intent' flow. The Autonomous domains (x and y) show 'Resource operations' with a 'Service closed loop' (3) and 'Resource intent' flow, each containing a 'Resource closed-loop' (4). Each operational layer includes a 'Copilot' and 'Agent' box with 'AI/GenAI (inference)'. An 'AI Center (AI/GenAI)' cloud is connected to the inference boxes. A legend at the bottom indicates the application of AI/GenAI in the three-layer architecture of AN.](81a4cbf0b3c4cbc065efdf8f800dadde_img.jpg)
-
-Application of AI/GenAI in the three-layer architecture of AN
-
-Figure 7: Full-stack AI/GenAI in the AN architecture. This diagram illustrates a three-layer architecture across four domains: Users, Commercialization, Production, and Autonomous domains. The Users layer includes 'Operations Efficiency' (Personalized Services, Automated O&M, Real time Experience) and 'Business Growth' (Smart City, Smart Home, Intelligent Manufacturing). The Commercialization layer shows 'Business operations' with a 'User closed loop' (1) and 'Business intent' flow. The Production layer shows 'Services operations' with a 'Business closed loop' (2) and 'Service intent' flow. The Autonomous domains (x and y) show 'Resource operations' with a 'Service closed loop' (3) and 'Resource intent' flow, each containing a 'Resource closed-loop' (4). Each operational layer includes a 'Copilot' and 'Agent' box with 'AI/GenAI (inference)'. An 'AI Center (AI/GenAI)' cloud is connected to the inference boxes. A legend at the bottom indicates the application of AI/GenAI in the three-layer architecture of AN.
-
-**Figure 7. Full-stack AI/GenAI in the AN architecture**
-
-GenAI can be used at any operational layer in the AN reference architecture and can work in tandem with other types of AI to develop two primary kinds of agent applications: role oriented copilots and scenario-based agents capable of acting on behalf of users or systems. This integration significantly enhances autonomous capabilities across all operational layers (business, service, and resource operations). The AN Reference Architecture inherently distributes intelligence and knowledge across all three operational layers, with each autonomous domain containing intelligence specific to its functions. As AI continues to evolve, the reference architecture remains stable and future-proof, incorporating new AI capabilities without requiring structural changes.
-
-## 2.4. AN Map / High-Value Scenarios
-
-The shift towards network automation and intelligence is a complex transformation involving multiple organizations, diverse networks, and the cooperation of different operators' platforms, systems, and multi-vendor devices. Historically, network improvements often focused on isolated innovations rather than a holistic approach,
-
-largely due to siloed departments and bottom-up methodologies. This fragmented approach hindered the streamlining of end-to-end network processes, ultimately slowing progress toward Autonomous Networks objectives.
-
-To address these challenges, the "AN Map" was initially introduced as a tool to help Communication Service Providers define clear AN objectives, break them down into actionable steps, and prioritize capability development. The AN Map also provided guidance on planning and deployment scope while serving as a reference point for tracking AN evolution and successes. As the understanding of AN development has matured, so has the terminology. The AN Map has evolved into the High-Value Scenarios (HVS) Matrix, reflecting a more structured and scenario-driven approach. Rather than being just a static reference, this transformation represents an ongoing activity, namely, AN scenario mapping, which provides a way to dimension and organize high-value scenarios across different network lifecycle phases and service domains.
-
-### 2.4.1. High-Value Scenarios and AN Scenario Mapping
-
-To construct the HVS Matrix, we first define AN implementation scenarios, leveraging methodologies such as value stream analysis and frameworks like TOGAF [12]. This process involves analyzing 11 operational flows across services and networks, which are then integrated with service categories and network domains.
-
-This structured approach forms the AN scenario framework, depicted in Figure 8, which helps define and prioritize AN high-value scenarios.
-
-![Figure 8: Mapping High-Value Scenarios Across Network, Service, and Operational Dimensions. The diagram shows a 3D coordinate system with three axes: Service (vertical, blue), Network (diagonal, green), and Operational Flow (horizontal, yellow). The Service axis lists categories: Individual Services, Home Services, Public-Sector and Enterprise Services, Wireless Network, Core Network, Fixed Access Network, Transport Network, and IP Network. The Network axis lists categories: Service marketing, Service delivery, Service assurance, Complaint handling, Network planning, Network deployment, Network change, Trouble shooting, Quality optimization, Energy efficiency optimization, and Resource management. The Operational Flow axis lists categories: Service marketing, Service delivery, Service assurance, Complaint handling, Network planning, Network deployment, Network change, Trouble shooting, Quality optimization, Energy efficiency optimization, and Resource management. Two 'High-value Scenario' points are marked: one at the intersection of Individual Services, Network planning, and Network deployment; and another at the intersection of Transport Network, Network planning, and Network deployment.](73dff6b45b2b9ffd384bab3235f869af_img.jpg)
-
-Figure 8: Mapping High-Value Scenarios Across Network, Service, and Operational Dimensions. The diagram shows a 3D coordinate system with three axes: Service (vertical, blue), Network (diagonal, green), and Operational Flow (horizontal, yellow). The Service axis lists categories: Individual Services, Home Services, Public-Sector and Enterprise Services, Wireless Network, Core Network, Fixed Access Network, Transport Network, and IP Network. The Network axis lists categories: Service marketing, Service delivery, Service assurance, Complaint handling, Network planning, Network deployment, Network change, Trouble shooting, Quality optimization, Energy efficiency optimization, and Resource management. The Operational Flow axis lists categories: Service marketing, Service delivery, Service assurance, Complaint handling, Network planning, Network deployment, Network change, Trouble shooting, Quality optimization, Energy efficiency optimization, and Resource management. Two 'High-value Scenario' points are marked: one at the intersection of Individual Services, Network planning, and Network deployment; and another at the intersection of Transport Network, Network planning, and Network deployment.
-
-**Figure 8. Mapping High-Value Scenarios Across Network, Service, and Operational Dimensions**
-
-### 2.4.2. Prioritize the Scenarios
-
-The AN scenario framework, as discussed in the previous section, defines a comprehensive set of high-value implementation scenarios necessary for improving the AN level and ultimately attaining higher levels of autonomy from an end-to-end perspective. However, in practical application, multiple rounds of iteration and evolution are often necessary to make the most of limited resources and experience.
-
-Hence, it is advisable to determine the priority of each AN high-value implementation scenario. This prioritization can be based on factors like the operator's service strategy, current autonomy status, and trends in service/network changes, as illustrated in Figure 9.
-
-![Figure 9: Four-quadrant analysis method for prioritize scenarios. The chart plots Tech Viability (Y-axis) against Business Value (X-axis). A horizontal dashed red line separates the quadrants. Scenarios are categorized into four groups: 'Good to have' (grey oval, low viability/low value), 'low-hanging fruits' (blue oval, medium viability/medium value), 'Quick win' (green oval, high viability/high value), and 'Must have' (yellow oval, low viability/high value). Specific scenarios include 'Network deployment', 'Consumer compliant handling', 'ToB quality enhancement', and 'ToB Problem Handling'.](0add961f6fd54a7ae5391d00c7e58f3c_img.jpg)
-
-The figure is a 2x2 matrix with 'Tech Viability' on the vertical axis and 'Business Value' on the horizontal axis. A horizontal dashed red line is positioned below the center. The quadrants are labeled as follows:
- 
-
-- Top-Left (High Viability, Low Value):** Labeled 'Good to have' in a grey box. It contains a grey oval labeled 'Network deployment' with several grey dots.
-- Top-Middle (High Viability, Medium Value):** Labeled 'low-hanging fruits' in a blue box. It contains a blue oval labeled 'Consumer compliant handling' with several blue dots.
-- Top-Right (High Viability, High Value):** Labeled 'Quick win' in a green box. It contains a green oval labeled 'ToB quality enhancement' with several green dots.
-- Bottom-Right (Low Viability, High Value):** Labeled 'Must have' in a yellow box. It contains a yellow oval labeled 'ToB Problem Handling' with several yellow dots.
-
-Figure 9: Four-quadrant analysis method for prioritize scenarios. The chart plots Tech Viability (Y-axis) against Business Value (X-axis). A horizontal dashed red line separates the quadrants. Scenarios are categorized into four groups: 'Good to have' (grey oval, low viability/low value), 'low-hanging fruits' (blue oval, medium viability/medium value), 'Quick win' (green oval, high viability/high value), and 'Must have' (yellow oval, low viability/high value). Specific scenarios include 'Network deployment', 'Consumer compliant handling', 'ToB quality enhancement', and 'ToB Problem Handling'.
-
-Figure 9. Four-quadrant analysis method for prioritize scenarios
-
-The four-quadrant analysis method as a recommendation for prioritizing scenarios can be used to classify each high-level implementation scenario based on the assessment of business value and technology viability. Then the AN map is finally established, by giving priority to high-value implementation scenarios, practitioners can effectively concentrate limited resources to maximize the goal achievement within a single iteration.
-
-Table 9 lists the AN L4 high-value scenarios in 2025-2027 described in L4 Blueprint [13].
-
-AN L4 high-value scenarios in 2025-2027 (Reference)
-
-|           | Service-oriented |                                | Individual Services                 | Home Services                       |                          | Enterprise Services                 |                                     |                          |                          |
-|-----------|------------------|--------------------------------|-------------------------------------|-------------------------------------|--------------------------|-------------------------------------|-------------------------------------|--------------------------|--------------------------|
-|           |                  |                                | 4G/5G                               | Home Broadband                      | ...                      | Private line                        | 5G2B                                | IOT                      | ...                      |
-| Lifecycle | Operation        | Service marketing              | <input type="checkbox"/>            | <input type="checkbox"/>            | <input type="checkbox"/> | <input type="checkbox"/>            | <input type="checkbox"/>            | <input type="checkbox"/> | <input type="checkbox"/> |
-|           |                  | Service delivery               | <input type="checkbox"/>            | <input type="checkbox"/>            | <input type="checkbox"/> | <input checked="" type="checkbox"/> | <input checked="" type="checkbox"/> | <input type="checkbox"/> | <input type="checkbox"/> |
-|           |                  | Service assurance              | <input checked="" type="checkbox"/> | <input checked="" type="checkbox"/> | <input type="checkbox"/> | <input checked="" type="checkbox"/> | <input checked="" type="checkbox"/> | <input type="checkbox"/> | <input type="checkbox"/> |
-|           |                  | Complaint handling             | <input checked="" type="checkbox"/> | <input checked="" type="checkbox"/> | <input type="checkbox"/> | <input type="checkbox"/>            | <input checked="" type="checkbox"/> | <input type="checkbox"/> | <input type="checkbox"/> |
-|           | Network-oriented |                                | Wireless                            | Core                                | Fixed access             | Transport                           | IP                                  | Others: e.g. Cloud       |                          |
-|           |                  |                                |                                     |                                     |                          |                                     |                                     |                          |                          |
-| Network   | Plan             | Network planning               | <input type="checkbox"/>            | <input type="checkbox"/>            | <input type="checkbox"/> | <input type="checkbox"/>            | <input type="checkbox"/>            | <input type="checkbox"/> | <input type="checkbox"/> |
-|           | Deployment       | Network deployment             | <input type="checkbox"/>            | <input type="checkbox"/>            | <input type="checkbox"/> | <input type="checkbox"/>            | <input type="checkbox"/>            | <input type="checkbox"/> | <input type="checkbox"/> |
-|           | Maintenance      | Fault management               | <input checked="" type="checkbox"/> | <input checked="" type="checkbox"/> | <input type="checkbox"/> | <input checked="" type="checkbox"/> | <input checked="" type="checkbox"/> | <input type="checkbox"/> | <input type="checkbox"/> |
-|           |                  | Network change                 | <input type="checkbox"/>            | <input checked="" type="checkbox"/> | <input type="checkbox"/> | <input checked="" type="checkbox"/> | <input checked="" type="checkbox"/> | <input type="checkbox"/> | <input type="checkbox"/> |
-|           | Optimization     | Quality optimization           | <input checked="" type="checkbox"/> | <input type="checkbox"/>            | <input type="checkbox"/> | <input type="checkbox"/>            | <input checked="" type="checkbox"/> | <input type="checkbox"/> | <input type="checkbox"/> |
-|           |                  | Energy efficiency optimization | <input checked="" type="checkbox"/> | <input type="checkbox"/>            | <input type="checkbox"/> | <input checked="" type="checkbox"/> | <input type="checkbox"/>            | <input type="checkbox"/> | <input type="checkbox"/> |
-|           |                  | Resource management            | <input type="checkbox"/>            | <input type="checkbox"/>            | <input type="checkbox"/> | <input type="checkbox"/>            | <input type="checkbox"/>            | <input type="checkbox"/> | <input type="checkbox"/> |
-|           |                  |                                | <input checked="" type="checkbox"/> | AN L4 high-value scenarios          |                          |                                     |                                     |                          |                          |
-
-Table 9. AN L4 High-Value Scenario mapping in 2025-2027 (Reference)
-
-# 3. Autonomous Networks Practice
-
-AN operational practices consist of two key activities: AN Strategic Planning (ANSP) and the AN Journey (refer to Figure 10).
-
-- AN Strategic Planning provides a structured approach for CSPs (or subgroups within CSPs) to define and guide their AN evolution. It includes corporate-level AN strategies, executive commitments, and guidance on implementing the four foundational elements of the Autonomous Network Framework. Additionally,
-- The AN Journey is an iterative process where operators implement strategies and continuously refine their approach to achieve their AN objectives. This distinction ensures that AN practices are understood as ongoing activities rather than static components.
-
-![Figure 10: AN Operational Practices diagram. The diagram is divided into two main sections: ANSP (Autonomous Network Strategic Planning) and AN Journey. ANSP includes inputs like CSPs' business strategies, high-level requirements, industry standards, and cutting-edge technologies, leading to an AN strategy (executives' commitment, AN blueprint, industry contributions, innovative technologies). This strategy is linked to four key elements: KPIs, Level standards, Target architecture, and AN map. The AN Journey is a continuous cycle starting with Assessment (Evaluation and objective formulation), followed by Gap analysis (Process walk-through and transformation items), then Solution design (System capability breakdown), and finally Implementation (Innovation pilot and replication), which feeds back into the Assessment stage. The AN map is a central component in the AN Journey cycle.](7e1c9b51e067a48cd0fcc9748d8bd8d8_img.jpg)
-
-Figure 10: AN Operational Practices diagram. The diagram is divided into two main sections: ANSP (Autonomous Network Strategic Planning) and AN Journey. ANSP includes inputs like CSPs' business strategies, high-level requirements, industry standards, and cutting-edge technologies, leading to an AN strategy (executives' commitment, AN blueprint, industry contributions, innovative technologies). This strategy is linked to four key elements: KPIs, Level standards, Target architecture, and AN map. The AN Journey is a continuous cycle starting with Assessment (Evaluation and objective formulation), followed by Gap analysis (Process walk-through and transformation items), then Solution design (System capability breakdown), and finally Implementation (Innovation pilot and replication), which feeds back into the Assessment stage. The AN map is a central component in the AN Journey cycle.
-
-**Figure 10. AN Operational Practices**
-
-To accelerate large-scale AN deployment, CSPs and their suppliers have devised a four-step continuous-improvement process based on high-value scenarios. By following this iterative process, operators can enhance their AN Level and effectiveness, and establish end-to-end service and business automation and autonomy.
-
-1. **Assessment:** for each high-value scenario, CSPs evaluate the live network based on the AN Level and KPIs, establish baselines for domain-specific AN Level and KPIs, and set improvement goals based on service requirements and the investment plan.
-2. **Gap analysis:** CSPs analyze the gaps between the baselines and goal, identify the root causes of breakpoints and weaknesses through process walk-through, break down the goal to achieve a higher AN Level and improve effectiveness, and formulate a key transformation item list.
-3. **Solution design:** based on the target architecture, CSPs convert capability requirements into function requirements; design an application architecture; categorize system functions; output process transformation requirements and function requirements for OSSs, OMCs, and NEs; create system development lists; and pilot solutions.
-4. **Implementation:** based on the system development list and pilot solutions, CSPs launch the solutions at opcos to facilitate the transition to production and replication among more opcos to improve their AN Level and KPIs and achieve the business goal.
-
-# 4. Terms & Abbreviations Used within this Document
-
-## 4.1. Terminology
-
-Terminology used in this document is defined in IG1258 Autonomous Networks Glossary v1.1.0. [6]. Some additional terminology used in this guide is defined below.
-
-| Term                               | Definition                                                                                                                                                                    |
-|------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| Autonomous Network Framework (ANF) | The TM Forum's Autonomous Network Framework is an implementation methodology designed to help CSPs plan and implement Autonomous Networks in an efficient and systematic way. |
-| O&M                                | Operations and Maintenance                                                                                                                                                    |
-| KCI                                | Key Capability Indicator                                                                                                                                                      |
-| KPI                                | Key Performance Indicator                                                                                                                                                     |
-| KEI                                | Key Effectiveness Indicator                                                                                                                                                   |
-
-# 5. References
-
-- [1] [Autonomous Networks Business Requirements and Framework \(IG1218\) – TM Forum](#)
-- [2] [Autonomous Networks – Reference Architecture \(IG1251\) – TM Forum](#)
-- [3] [Autonomous Network Levels Evaluation Methodology \(IG1252\) – TM Forum](#)
-- [4] [IG1256 Autonomous Network Effectiveness Indicators – TM Forum](#)
-- [5] [IG1251A Autonomous Networks Reference Architecture Realizations – TM Forum](#)
-- [6] [IG1258 Autonomous Networks Glossary – TM Forum](#)
-- [7] [TS28.100 Management and orchestration; Levels of autonomous network, 3GPP](#)
-- [8] [Autonomous Networks: Empowering digital transformation – from strategy to implementation \(IG1305\) – TM Forum](#)
-- [9] [Autonomous Networks: Empowering digital transformation – evolving from Level 2/3 towards Level 4 \(IG1326\) – TM Forum](#)
-- [10] [GB935 Metrics Framework R19.0.1](#)
-- [11] [GB988 TM Forum Metrics Definitions v21.5 – TM Forum](#)
-- [12] [The TOGAF Standard, 10th Edition, The Open Group](#)
-- [13] [IG1401 TM Forum AN Journey Guide: Level 4 industry blueprint high-value scenarios](#)
-
-# 6. Administrative Appendix
-
-## 6.1. Document History
-
-### 6.1.1. Version History
-
-| Version Number | Date Modified | Modified by:                                                                              | Description of changes           |
-|----------------|---------------|-------------------------------------------------------------------------------------------|----------------------------------|
-| 0.9.0          | 01-Oct-2023   | Kevin Xu, APAC Program Director, TM Forum<br><br>Kevin McDonnell, Senior Director, Huawei | First Draft                      |
-| 1.0.0          | 17-Oct-2023   | Alan Pope                                                                                 | Final edits prior to publication |
-| 1.1.0          | 04-Jul-2024   | Alan Pope                                                                                 | Final edits prior to publication |
-| 1.2.0          | 10-Jan-2025   | Alan Pope                                                                                 | Final edits prior to publication |
-| 2.0.0          | 14-Mar-2025   | Yuan Yao, Wu Yunhe, Kevin McDonnell                                                       | Revisions to section 2.3         |
-
-### 6.1.2. Release History
-
-| Release Status | Date Modified | Modified by:     | Description of changes                      |
-|----------------|---------------|------------------|---------------------------------------------|
-| Pre-production | 17-Oct-2023   | Alan Pope        | Initial Release                             |
-| Pre-production | 20-Nov-2023   | Adrienne Walcott | Updated to Member Evaluated status          |
-| Pre-production | 04-Jul-2024   | Alan Pope        | Updated to v1.1.0                           |
-| Production     | 30-Aug-2024   | Adrienne Walcott | Updated to reflect TM Forum Approved status |
-| Pre-production | 10-Jan-2025   | Alan Pope        | Updated to v1.2.0                           |
-| Production     | 07-Mar-2025   | Adrienne Walcott | Updated to reflect TM Forum Approved status |
-| Pre-production | 14-Mar-2025   | Alan Pope        | Updated to v2.0.0                           |
-| Production     | 09-May-2025   | Adrienne Walcott | Updated to reflect TM Forum Approved status |
-
-## 6.2. Acknowledgments
-
-This document was prepared by the members of the TM Forum Autonomous Networks team.
-
-| Team Member (@mention)                    | Company      | Role*                         |
-|-------------------------------------------|--------------|-------------------------------|
-| <a href="#">Kevin Xu</a>                  | TM Forum     | Author                        |
-| <a href="#">Kevin McDonnell</a>           | Huawei       | Author, Editor, Project Chair |
-| <a href="#">Hui Li</a>                    | Huawei       | Editor, Key Contributor       |
-| <a href="#">guangying zheng</a>           | Huawei       | Editor, Key Contributor       |
-| <a href="#">Yuan Yao</a>                  | China Mobile | Key Contributor               |
-| <a href="#">JUAN ANDRÉS SUELS CARDOZO</a> | Telefónica   | Key Contributor               |
-| <a href="#">Asser EL NAHAS</a>            | Orange       | Key Contributor               |
-| <a href="#">Chao Wu</a>                   | NTT          | Key Contributor               |
-| <a href="#">Yunhe Wu</a>                  | Huawei       | Key Contributor               |
-| <a href="#">Xiao Hongmei</a> (Malina)     | Inspur       | Reviewer                      |
-| <a href="#">Dmytro Gassanov</a>           | TM Forum     | Reviewer                      |
-| <a href="#">Alan Pope</a>                 | TM Forum     | Reviewer, Editor              |
-
-\*Select from: Project Chair, Project Co-Chair, Author, Editor, Key Contributor, Additional Input, Reviewer

marked/Autonomous_Networks/IG1230A_Autonomous_Networks_Scenario_Realizations_v1.1.0/raw.md

@@ -1,565 +0,0 @@
-
-
-# TM Forum Introductory Guide
-
-# Autonomous Networks Scenario Realizations
-
-**IG1230A**
-
-**Team Approval Date: 28-May-2021**
-
-|                                   |                                           |
-|-----------------------------------|-------------------------------------------|
-| <b>Release Status: Production</b> | <b>Approval Status: TM Forum Approved</b> |
-| <b>Version 1.1.0</b>              | <b>IPR Mode: RAND</b>                     |
-
-## Notice
-
-Copyright © TM Forum 2021. All Rights Reserved.
-
-This document and translations of it may be copied and furnished to others, and derivative works that comment on or otherwise explain it or assist in its implementation may be prepared, copied, published, and distributed, in whole or in part, without restriction of any kind, provided that the above copyright notice and this section are included on all such copies and derivative works. However, this document itself may not be modified in any way, including by removing the copyright notice or references to TM FORUM, except as needed for the purpose of developing any document or deliverable produced by a TM FORUM Collaboration Project Team (in which case the rules applicable to copyrights, as set forth in the [TM FORUM IPR Policy](#), must be followed) or as required to translate it into languages other than English.
-
-The limited permissions granted above are perpetual and will not be revoked by TM FORUM or its successors or assigns.
-
-This document and the information contained herein is provided on an “AS IS” basis and TM FORUM DISCLAIMS ALL WARRANTIES, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF THE INFORMATION HEREIN WILL NOT INFRINGE ANY OWNERSHIP RIGHTS OR ANY IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.
-
-TM FORUM invites any TM FORUM Member or any other party that believes it has patent claims that would necessarily be infringed by implementations of this TM Forum Standards Final Deliverable, to notify the TM FORUM Team Administrator and provide an indication of its willingness to grant patent licenses to such patent claims in a manner consistent with the IPR Mode of the TM FORUM Collaboration Project Team that produced this deliverable.
-
-The TM FORUM invites any party to contact the TM FORUM Team Administrator if it is aware of a claim of ownership of any patent claims that would necessarily be infringed by implementations of this TM FORUM Standards Final Deliverable by a patent holder that is not willing to provide a license to such patent claims in a manner consistent with the IPR Mode of the TM FORUM Collaboration Project Team that produced this TM FORUM Standards Final Deliverable. TM FORUM may include such claims on its website but disclaims any obligation to do so.
-
-TM FORUM takes no position regarding the validity or scope of any intellectual property or other rights that might be claimed to pertain to the implementation or use of the technology described in this TM FORUM Standards Final Deliverable or the extent to which any license under such rights might or might not be available; neither does it represent that it has made any effort to identify any such rights. Information on TM FORUM's procedures with respect to rights in any document or deliverable produced by a TM FORUM Collaboration Project Team can be found on the TM FORUM website. Copies of claims of rights made available for publication and any assurances of licenses to be made available, or the result of an attempt made to obtain a general license or permission for the use of such proprietary rights by implementers or users of this TM FORUM Standards Final Deliverable, can be obtained from the TM FORUM Team Administrator. TM FORUM makes no representation that any information or list of intellectual property rights will at any time be complete, or that any claims in such list are, in fact, Essential Claims.
-
-Direct inquiries to the TM Forum office:
-
-181 New Road, Suite 304  
-Parsippany, NJ 07054 USA  
-Tel No. +1 862 227 1648  
-TM Forum Web Page: [www.tmforum.org](http://www.tmforum.org)
-
-# Table of Contents
-
-|                                                                                                    |           |
-|----------------------------------------------------------------------------------------------------|-----------|
-| <b>Notice.....</b>                                                                                 | <b>2</b>  |
-| <b>Table of Contents.....</b>                                                                      | <b>4</b>  |
-| <b>List of Figures.....</b>                                                                        | <b>5</b>  |
-| <b>List of Tables.....</b>                                                                         | <b>6</b>  |
-| <b>1 AN Scenario Realizations.....</b>                                                             | <b>7</b>  |
-| 1.1 Introduction.....                                                                              | 7         |
-| <b>2 An Example of Self-Healing Capability.....</b>                                                | <b>8</b>  |
-| 2.1 Realizations.....                                                                              | 8         |
-| 2.2 Simple ‘Canonical’ Pattern.....                                                                | 8         |
-| 2.3 Recursive Pattern.....                                                                         | 9         |
-| <b>3 Electric Vehicle (EV) charging infrastructure business continuity solution .....</b>          | <b>11</b> |
-| 3.1 Customer Requirements.....                                                                     | 11        |
-| 3.2 AN Business Capabilities needed to support Services.....                                       | 12        |
-| 3.3 Services .....                                                                                 | 14        |
-| 3.4 Business Capabilities.....                                                                     | 16        |
-| 3.5 Using the AN Framework.....                                                                    | 17        |
-| <b>4 Use Cases using AN Level Evaluation Methodology .....</b>                                     | <b>18</b> |
-| 4.1 Level Evaluation for IPRAN Assurance.....                                                      | 18        |
-| 6.1.1 Task Criteria for monitoring and troubleshooting of IPRAN network of mobile 2C services..... | 19        |
-| 4.1.2 Evaluation Method.....                                                                       | 20        |
-| 4.1.3 Example of evaluation object AN level.....                                                   | 21        |
-| 4.2 Level Evaluation for HBB Intelligent O&M.....                                                  | 21        |
-| 4.2.1 Operation process and operation tasks .....                                                  | 22        |
-| 4.2.2 Metrics and Capabilities criteria.....                                                       | 24        |
-| 4.2.3 Evaluation Method .....                                                                      | 25        |
-| <b>5. Administrative .....</b>                                                                     | <b>26</b> |
-| 5.1 Document History.....                                                                          | 26        |
-| 5.1.1 Version History .....                                                                        | 26        |
-| 5.1.2 Release History.....                                                                         | 26        |
-| 5.2 Acknowledgments .....                                                                          | 26        |
-| 5.2.1 Guide Lead & Author .....                                                                    | 26        |
-| 5.2.2 Main Contributors .....                                                                      | 26        |
-| 5.2.3 Additional Inputs .....                                                                      | 27        |
-| 5.2.4 TM Forum Staff.....                                                                          | 27        |
-
-# List of Figures
-
-|                                                                                 |    |
-|---------------------------------------------------------------------------------|----|
-| Figure 2-1 Implementation functions for Autonomous Domains.....                 | 9  |
-| Figure 2-2 Recursive Pattern applied at Business level.....                     | 10 |
-| Figure 3-3 EV Charging Ecosystem .....                                          | 12 |
-| Figure 3-2 5G Ride On! 2020 Catalyst using AN Framework.....                    | 17 |
-| Figure 4-1 Home broadband O&M requirements architecture.....                    | 22 |
-| Figure 4-2 Operational processes home broadband O&M use cases.....              | 22 |
-| Figure 4-3 Fault Prediction and Prevention workflow .....                       | 23 |
-| Figure 4-4 Relationship between service KPI, use cases, and technical KPI ..... | 24 |
-
-# List of Tables
-
-|                                                                                                                         |    |
-|-------------------------------------------------------------------------------------------------------------------------|----|
-| Table 1 EV Charging infrastructure requirements, metrics, and business capabilities.....                                | 12 |
-| Table 2 Level Evaluation for monitoring and troubleshooting of IPRAN .....                                              | 19 |
-| Table 3 Level Evaluation for monitoring and troubleshooting of IPRAN network.....                                       | 20 |
-| Table 4 Evaluate the level of each task for monitoring and troubleshooting.....                                         | 20 |
-| Table 5 Task of UC1-“HBB Fault Prediction and Prevention” .....                                                         | 23 |
-| Table 6 Task level evaluation reference criteria for AN level of “HBB Proactive Faults Prediction and Prevention” ..... | 25 |
-
-# 1 AN Scenario Realizations
-
-## 1.1 Introduction
-
-Autonomous Network practices can improve both the operational efficiency and end-user experience of today's operator use case. This guide describes scenario realizations of operator use cases using an autonomy mindset and, in particular, the mechanisms described in the AN technical architecture (IG1230). Using closed control feedback and intent-driven interactions, we can deploy smart software to continuously monitor and optimize the networks.
-
-Autonomous Networks have become a prerequisite for many more advanced use-cases. For example, with 5G and Software-Defined Networks, often the topology of the network itself is dynamic: higher-level application services dynamically change their network requirements in the same way as cloud-computing applications elastically change their compute requirements. Autonomous Networks can enable concepts like Digital Twins that allow you to model and dynamically simulate changes to a Network to de-risk such changing requirements.
-
-Another example is for mission-critical services that require the network to be "in the loop". An Autonomous Network can interact with the higher-level mission-critical service through APIs to warn of potential service interruptions. An autonomous vehicle could, for example, be warned about crossing an international/roaming boundary and the vehicle could adopt a limited-network mode where it drives more slowly. For industries like healthcare, aviation, and transport, Autonomous Networks must support the move from "best-effort" networks to ultra-reliable "network-in-the-loop" services. This section describes several real-world examples of where operator use cases and requirements were realized using the core concepts of the AN technical architecture.
-
-# 2 An Example of Self-Healing Capability
-
-## 2.1 Realizations
-
-The following sections describe examples of how AN Technical Architecture can be practically realized by some implementation functions:
-
-- Business Service Controller
-- Service Status
-- Elements delivering the service ( managed elements)
-- Intelligence Management
-
-## 2.2 Simple ‘Canonical’ Pattern
-
-The flow for how these implementation features implemented self-healing are described below:
-
-- Start the service running using TMF640 service configuration and activation or TMF664 resource function activation – includes the “intent” parameters.
-- Service controller will start a service element **START SERVICE**
-- Service element will start producing outputs (TMF635) and performance statistics (TMF628) **PRODUCE SERVICE STATUS**
-- The internal service monitor will read the status and compare it against the service intent **MONITOR SERVICE**
-- If the intent is not being achieved, then based on analytics, ML or AI the service controller will attempt to achieve the intent by either reconfiguring the service or starting a new service element **REPAIR SERVICE**
-- Closed loop control is delivered within the domain. **CLOSED LOOP CONTROL**
-
-![Figure 2-1: Implementation functions for Autonomous Domains. The diagram illustrates the interaction between Intelligence Management, Domain automation, and various TMF standards. Intelligence Management (AI/ML functions and AI Models) interacts with the Domain automation (Element of component that is controlling the service). The Domain automation includes a Programmable service controller (analytic/ML/AI based) which manages Start, Configure, and Monitor services. This controller interacts with the Service status (Read status) and the Instance of element of component that is delivering the service (Write status). The Instance of element interacts with TMF628 Performance Management and TMF635 Service Usage. The Domain automation also interacts with TMF640 Service Activation Configuration <config> or TMF664 Resource Function Activation <config>.](562f471e8153729557e6a4ee6343c32c_img.jpg)
-
-The diagram illustrates the implementation functions for Autonomous Domains, showing the interaction between Intelligence Management, Domain automation, and various TMF standards.
-
-**Intelligence Management** (left) includes **AI/ML functions** and **AI Models**. It interacts with the **Domain automation** (center) via a dashed red box.
-
-**Domain automation** (center) is a red box containing the **Element of component that is controlling the service**. This element includes a **Programmable service controller (analytic/ML/AI based)** which manages **Start service**, **Configure service**, and **Monitor service**. The controller interacts with the **Service status** (right) via **Read status** and **Write status** messages. The controller also interacts with the **Instance of element of component that is delivering the service (could be CFS or RFS)** (bottom right) via **Modify element instance <config>** and **Start element instance** messages.
-
-The **Service status** (right) interacts with **TMF628 Performance Management** (top right) via a double-headed arrow. The **Instance of element of component that is delivering the service** (bottom right) interacts with **TMF635 Service Usage** (top right) via a double-headed arrow.
-
-The **Domain automation** (center) interacts with **TMF640 Service Activation Configuration <config> or TMF664 Resource Function Activation <config>** (top left) via a double-headed arrow.
-
-Figure 2-1: Implementation functions for Autonomous Domains. The diagram illustrates the interaction between Intelligence Management, Domain automation, and various TMF standards. Intelligence Management (AI/ML functions and AI Models) interacts with the Domain automation (Element of component that is controlling the service). The Domain automation includes a Programmable service controller (analytic/ML/AI based) which manages Start, Configure, and Monitor services. This controller interacts with the Service status (Read status) and the Instance of element of component that is delivering the service (Write status). The Instance of element interacts with TMF628 Performance Management and TMF635 Service Usage. The Domain automation also interacts with TMF640 Service Activation Configuration  or TMF664 Resource Function Activation .
-
-Figure 2-1 Implementation functions for Autonomous Domains
-
-## 2.3 Recursive Pattern
-
-This simple implementation of a ‘canonical’ model can be applied recursively to each layer (see Figure 2-2). The flow in this case
-
-- Start each of the required service domains running using TMF622 Product order – includes the “intent” parameters.
-- Customer order orchestration and distribution will activate a set of TMF641 Service Order management and start a set of service domains **START BUSINESS SERVICE**
-
-![Figure 2-2 Recursive Pattern applied at Business Operations layer. The diagram illustrates a recursive pattern for business operations. At the top, 'Intelligence Management' (containing 'AI/ML functions' and 'AI Models') interacts with the 'Business Automation' layer. The 'Business Automation' layer is represented by a dashed red box containing a 'Business Service Controller' and a 'Business Service Instance'. The 'Business Service Controller' includes a 'Programmable service controller (analytic/ML/AI based)' with 'Start service', 'Configure service', and 'Monitor service' functions. It also has a 'Status' block. The 'Business Service Instance' is connected to the controller. External interactions include 'TMF622 Product Order <config>' (downward arrow), 'TMF623 SLA Management' (bidirectional arrow), and 'TMF635 Service Usage' (upward arrow). Below the main components, three smaller boxes show the recursive pattern applied at the network layer, each containing a 'Network Automation' block and a 'Network Service Instance'.](cfda9df1319e04207eb28bcefd1dab7b_img.jpg)
-
-Figure 2-2 Recursive Pattern applied at Business Operations layer. The diagram illustrates a recursive pattern for business operations. At the top, 'Intelligence Management' (containing 'AI/ML functions' and 'AI Models') interacts with the 'Business Automation' layer. The 'Business Automation' layer is represented by a dashed red box containing a 'Business Service Controller' and a 'Business Service Instance'. The 'Business Service Controller' includes a 'Programmable service controller (analytic/ML/AI based)' with 'Start service', 'Configure service', and 'Monitor service' functions. It also has a 'Status' block. The 'Business Service Instance' is connected to the controller. External interactions include 'TMF622 Product Order ' (downward arrow), 'TMF623 SLA Management' (bidirectional arrow), and 'TMF635 Service Usage' (upward arrow). Below the main components, three smaller boxes show the recursive pattern applied at the network layer, each containing a 'Network Automation' block and a 'Network Service Instance'.
-
-Figure 2-2 Recursive Pattern applied at Business Operations layer
-
-- Service domains will start producing outputs(TMf635) and performance statistics (TMf628) **PRODUCE BUSINESS SERVICE STATUS**
-- The internal business service monitor will read the status and compare them against the business service intent **MONITOR BUSINESS SERVICE**
-- If the business intent is not being achieved, then based on analytics, ML or AI the business service controller will attempt to achieve the intent by either reconfiguring the network service or starting a new network service **REPAIR BUSINESS SERVICE**
-- Closed loop control is delivered within the business domain and between the business layer, the network layer and the resource layer. **CROSS LAYER CLOSED LOOP CONTROL**
-
-# 3 Electric Vehicle (EV) charging infrastructure business continuity solution
-
-|                     |                                                                                                                                                           |
-|---------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
-| <b>Catalyst</b>     | <b>5G Ride On! (TM Forum Catalyst 2020)</b><br><b>Electric vehicle charging infrastructure business continuity solution</b>                               |
-| <b>Champions</b>    | BT, Orange, Telecom Italia                                                                                                                                |
-| <b>Participants</b> | MDS Group (BSS/CRM)<br>Incognito Software Systems (OSS/Service Activation)<br>TEOCO (OSS/Service Assurance)<br>Huawei (Network Technology and Management) |
-
-## 3.1 Customer Requirements
-
-- 1) The EV charging customer journey is both a physical journey and an online journey and involves a complex business ecosystem (see Figure 3-3) to make it work. The ecosystem is heavily reliant on connectivity services, and oftentimes communication issues (especially outages) won't go unnoticed by customers. This challenge presents a differentiation opportunity for those who have continuity plans for all scenarios. Connectivity and connectivity related services are needed to enable the EV charging customer journey in several ways:
-  - Finding nearby public charge points and checking their availability, connector compatibility, charge level, and in some cases: booking a charging time slot.
-  - [In the event the driver is outside their local area] navigating to the selected public charge point using one of the many mobile navigation apps (Google Maps, TomTom Go, HERE WeGo, Sygic, etc.)
-  - Performing a payment pre-authorization to unlock the EV charging station equipment. This is a key difference with the gasoline-based car industry: network connectivity is not required to pump gas, it is for the electric car industry (the one exception being home charger).
-
-![Figure 3-1 EV Charging Ecosystem diagram showing the flow of energy, data, and services between various stakeholders.](042733dc5e8e7f5f30b60adba3266cde_img.jpg)
-
-The diagram illustrates the EV Charging Ecosystem, divided into five main functional areas: ENERGY CONVERSION, ENERGY TRANSFER FROM/TO EV, SERVICE PROVIDERS, INFORMATION PROVIDERS, and ELECTRIC EV USER VEHICLE PREMISES.
-
-- ENERGY CONVERSION:** Includes the Energy Supplier, Distribution System Operator, and Transmission System Operator. The Energy Supplier provides energy to the Charging Station Operator. The Distribution System Operator provides transmission grid infrastructure to the Charging Station Operator. The Transmission System Operator provides distribution grid infrastructure to the Charging Station Operator.
-- ENERGY TRANSFER FROM/TO EV:** The Charging Station Operator provides energy to the EV User. The EV User drives the vehicle.
-- SERVICE PROVIDERS:** Includes the E-Mobility Clearing House, E-Mobility Service Provider, Cloud Provider, and CSP. The E-Mobility Clearing House handles payment transaction settlement and roaming. The E-Mobility Service Provider offers services and billing. The Cloud Provider hosts the app on. The CSP provides business continuity services and 5G assure service.
-- INFORMATION PROVIDERS:** Includes the App Provider, Emergency Coordinator, and Weather/Met Service. The App Provider provides the charge app and offers services and billing. The Emergency Coordinator provides weather predictions and warnings. The Weather/Met Service provides weather predictions and warnings.
-- ELECTRIC EV USER VEHICLE PREMISES:** The EV User uses the app to find the nearest charge point.
-
-Legend:
-
-- Infrastructure (Grey arrow)
-- Energy (Green arrow)
-- Data (Blue arrow)
-- Financial Services (Monetization) (Red arrow)
-- Communication & IT (Black arrow)
-
-Figure 3-1 EV Charging Ecosystem diagram showing the flow of energy, data, and services between various stakeholders.
-
-Figure 3-1 EV Charging Ecosystem
-
-If any of the above have an issue they can debilitate the EV charging customer journey, and result in lost revenue for charge point station operators. This has consequences across the broader ecosystem. Thus, a differentiated business continuity solution offering from a CSP (or even a group of CSPs working together) can help better address these pain points and enable a smoother customer experience.
-
-The solution addresses two requirements addressed by different autonomous services, as outlined in Table 1. Note that the business capabilities are per reference guide [IG1218], and the Self-X capability applies to all of them.
-
-## 3.2 AN Business Capabilities needed to support Services
-
-Table 1 EV Charging infrastructure requirements, metrics, and business capabilities
-
-| Service                       | Autonomous Network Requirements, Metrics, & Business Capabilities                                                    |                                                                                                     |                                                                                                                    |                                                                                                       |
-|-------------------------------|----------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------|
-|                               | User perspective                                                                                                     | Business perspective                                                                                | Service perspective                                                                                                | Network/ICT perspective                                                                               |
-|                               | Self-X                                                                                                               |                                                                                                     |                                                                                                                    |                                                                                                       |
-| <b>Assured location-based</b> | <b>Requirements</b> <ul style="list-style-type: none"> <li>Find local EV charging points and their latest</li> </ul> | <b>Requirements</b> <ul style="list-style-type: none"> <li>Advertise Chargepoint status,</li> </ul> | <b>Requirements</b> <ul style="list-style-type: none"> <li>Provide reliable and secure connectivity for</li> </ul> | <b>Requirements</b> <ul style="list-style-type: none"> <li>Provide on-demand onboarding of</li> </ul> |
-
-| Service                     | Autonomous Network Requirements, Metrics, & Business Capabilities                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
-|-----------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-|                             | User perspective                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              | Business perspective                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        | Service perspective                                                                                                                                                                                                                                                                                                                                                                                                                                                                 | Network/ICT perspective                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
-| <b>information service</b>  | <p>information using a location-based app (mobile, car dashboard)</p> <ul style="list-style-type: none"> <li>• Book a timeslot at a specific charge point.</li> <li>• Route to selected EV chargepoint station</li> </ul> <p><b>Metrics</b></p> <ul style="list-style-type: none"> <li>• Load speed</li> </ul> <p><b>Business Capabilities</b></p> <ul style="list-style-type: none"> <li>• Location awareness</li> <li>• Context-awareness</li> <li>• Automatic navigation</li> <li>• Online service selection</li> <li>• Online service ordering</li> </ul> | <p>availability, and price information to prospective customers.</p> <ul style="list-style-type: none"> <li>• Chargepoint Information must be consistently up-to-date to meet end-user expectations</li> </ul> <p><b>Metrics</b></p> <ul style="list-style-type: none"> <li>• Chargepoint Info publish success rate.</li> <li>• Time since the last Chargepoint info publish.</li> </ul> <p><b>Business Capabilities</b></p> <ul style="list-style-type: none"> <li>• Channel management</li> <li>• Partner management</li> <li>• Product management</li> <li>• Agreement management</li> <li>• Order management</li> </ul> | <p>periodic Chargepoint data transfers.</p> <ul style="list-style-type: none"> <li>• Make local information service available in specific geographical areas in the event of an outage.</li> </ul> <p><b>Metrics</b></p> <ul style="list-style-type: none"> <li>• Information service availability</li> </ul> <p><b>Business Capabilities</b></p> <ul style="list-style-type: none"> <li>• Network management</li> <li>• Incident management</li> <li>• Asset management</li> </ul> | <p>application to targeted MEC data centers for temporary use.</p> <ul style="list-style-type: none"> <li>• Assure availability of application across MEC data centers.</li> </ul> <p><b>Metrics</b></p> <ul style="list-style-type: none"> <li>• MEC platform availability</li> <li>• MEC host availability</li> <li>• MEC application availability</li> <li>• Mobile slice accessibility</li> <li>• Mobile slice traffic volume</li> </ul> <p><b>Business Capabilities</b></p> <ul style="list-style-type: none"> <li>• Network design</li> <li>• Application onboarding</li> <li>• Application lifecycle management</li> <li>• Network performance management</li> <li>• Incident management</li> </ul> |
-| <b>Assured connectivity</b> | <p><b>Requirements</b></p> <ul style="list-style-type: none"> <li>• Pre-authenticate for payment and charge electric vehicle 24-7-365</li> <li>• Frictionless transaction: cashless, secure payment, no human contact needed, email receipt available if required.</li> </ul> <p><b>Metrics</b></p>                                                                                                                                                                                                                                                           | <p><b>Requirements</b></p> <ul style="list-style-type: none"> <li>• Provide efficient reliable service whenever needed.</li> <li>• Maximize kWh output per chargepoint.</li> <li>• Minimize the number of support staff required to run EV chargepoint facility.</li> </ul>                                                                                                                                                                                                                                                                                                                                                 | <p><b>Requirements</b></p> <ul style="list-style-type: none"> <li>• Provide a highly resilient connectivity solution to meet the needs of the EV chargepoint operator.</li> <li>• Provide redundant connectivity option in event of an outage.</li> <li>• Minimize the resource cost of</li> </ul>                                                                                                                                                                                  | <p><b>Requirements</b></p> <ul style="list-style-type: none"> <li>• Provide robust connectivity solutions for fixed and wireless.</li> <li>• Scale capacity with demand (i.e., up or down as required)</li> </ul> <p><b>Metrics</b></p> <ul style="list-style-type: none"> <li>• Fixed Access availability</li> </ul>                                                                                                                                                                                                                                                                                                                                                                                      |
-
-| Service              | Autonomous Network Requirements, Metrics, & Business Capabilities                                                                                                                                                                                        |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
-|----------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-|                      | User perspective                                                                                                                                                                                                                                         | Business perspective                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      | Service perspective                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          | Network/ICT perspective                                                                                                                                                                                                                                                                                                                                                                                                                                    |
-| Assured connectivity | <ul style="list-style-type: none"> <li>• Customer satisfaction</li> <li>• No of Customer complaints</li> </ul> <b>Business Capabilities</b> <ul style="list-style-type: none"> <li>• Order management (self-ordering)</li> <li>• Self-service</li> </ul> | <b>Metrics</b> <ul style="list-style-type: none"> <li>• Chargepoint availability</li> <li>• Chargepoint utilization</li> <li>• Transaction success rate</li> <li>• Average/Std dev transaction duration</li> <li>• #Security incidents</li> <li>• #Customer complaints</li> <li>• Net Promoter Score</li> <li>• #Staff : #Chargepoint Ratio</li> </ul> <b>Business Capabilities</b> <ul style="list-style-type: none"> <li>• Customer authentication and authorization</li> <li>• Customer information management</li> <li>• Partner management</li> <li>• Asset lifecycle management</li> <li>• Asset risk management</li> <li>• Product lifecycle management</li> </ul> | providing redundant connectivity option.<br><br><b>Metrics</b> <ul style="list-style-type: none"> <li>• Service accessibility</li> <li>• Network availability</li> <li>• Network failover success rate</li> </ul> <b>Business Capabilities</b> <ul style="list-style-type: none"> <li>• Order management</li> <li>• Product management</li> <li>• Product lifecycle management</li> <li>• Network performance management</li> <li>• Incident management</li> <li>• Partner management</li> <li>• </li> </ul> | <ul style="list-style-type: none"> <li>• Mobile slice accessibility</li> <li>• Scaling success rate</li> <li>• Traffic volume</li> <li>• Security incident rate</li> </ul> <b>Business Capabilities</b> <ul style="list-style-type: none"> <li>• Network design</li> <li>• Network activation</li> <li>• Network matching</li> <li>• Network performance management</li> <li>• Network risk management</li> <li>• Network compliance management</li> </ul> |
-
-## 3.3 Services
-
-To address the pain points and challenges mentioned, the following services are provided:
-
-- *Online service selection and information: EV drivers can use a mobile or in-car dashboard application to locate the nearest charging stations providing charging services. Drivers can also see all details and status of the chargepoint infrastructure (e.g., what type of connectors are supported, how much power is available to discharge, usage state)*
-- *Online service ordering: EV drivers can use a mobile or in-car dashboard application to book a timeslot at a specific chargepoint.*
-- *Zero-touch payment: EV drivers can swipe a fob or card to authenticate for payment. The chargepoint then communicates over the network to the chargepoint management system which authenticates the account and subsequently unlocks the chargepoint. The charge to the customer account is applied after the vehicle has been charged.*
-- *After the charge is completed the customer can opt to receive an email with a sales receipt.*
-- *Agile deployment: The AN stack uses all-scenario automation capabilities to implement intelligent service orchestration, resource orchestration, and process orchestration, improving network deployment agility and implementing process scheduling and orchestration of atomic capabilities. Automated modeling from service requirements to slice and MEC resources, automatic online network resource evaluation, one-click slice deployment, and automatic slice configuration, automated service testing quickly implements automatic closed loop in all scenarios during network O&M and meets the requirements of agile provisioning of electric power services in the industry market.*
-- *Intelligent O&M: The AN stack uses technologies such as neural networks and knowledge graphs to automatically provide optimal intelligent O&M policies. It uses ML-derived dynamic thresholds, KPI association analysis, and automatic sub-health detection to detect and provide notification of faults in advance, and AI-based fast fault locating and slice self-healing.*
-- *Intelligent failover: The AN stack performs self-monitoring of both fixed and wireless networks involved in the business continuity solution. In the event of a fixed network outage, a wireless network slice is available and self-scaling is used to grow the size of the slice as needed, maximizing resource efficiency. If the geographical area of the fixed network outage grows the AN will perform automatic resource matching with the wireless network and automatically adds the relevant wireless to the scope of the network slice.*
-- *Network outage prediction: AI-based network performance functions within the AN use weather and other IoT sensor data to make predictions on future weather conditions on how it will impact the network and network services.*
-
-- *Auto application onboarding: At service order time the AN keeps a record of the mobile application used to serve consumers charging point information. This application would normally run in a centralized public cloud. If a network outage prediction is made that is deemed to impact the EV charging infrastructure the application is onboarded into the appropriate MEC data centers.*
-- *Zero-trust DDoS in MEC: Within wireless and core networks there are backoff and access barring mechanisms that detect and prevent denial of service attacks. These mechanisms are governed by configuration. AI algorithms can be used to further optimize these parameters in the event of ever more sophisticated attacks.*
-
-## 3.4 Business Capabilities
-
-To address the pain points and challenges mentioned, the following business capabilities are provided. While the term not mentioned explicitly below these are fortified with “Zero X” capabilities in the context of AN.
-
-**Customer management:** This capability provides the ability to control, predict, process, organize, present, and analyze all information, documents, preferences, experiences, and history related to an individual or organization that has, plans to have, or has had an account with the business. It encompasses several other detailed capabilities such as definition, authentication and authorization, preference management, portfolio management, customer matching, and customer information management. A few (not all) are mentioned below.
-
-**Customer authentication and authorization:** This capability provides the ability to verify customer identity and access rights in the context of a given business scenario and allow a customer to proceed based on those rights or otherwise prevent the customer from proceeding.
-
-**Customer information management:** This capability provides the ability to organize, track, report on or otherwise disseminate attributes, data, and other perspectives about a customer.
-
-**Order management:** This capability provides the ability to place, validate, cancel, change, track, fulfill, and otherwise manage a request by one party to another to buy, sell, or exchange goods or services.
-
-**Incident management:** The capability provides the ability to detect, collect data on, organize, respond and remediate reported troubles/incidents.
-
-**Product management:** The capability provides the ability to conceptualize, design, develop, bundle, price, launch, maintain and retire goods and services offered by the business.
-
-**Network management:** The capability provides the ability to design the architecture and plan, develop, deploy, monitor, and report on the network infrastructure. It encompasses several other detailed capabilities such as design, lifecycle management, performance management, compliance management, access management, A few (not all) are mentioned below.
-
-**Network design:** This capability provides the ability to conceptualize, specify, and model features that a network should have. From an AN perspective, the designs would be automatically generated based on network intent and verified.
-
-**Network compliance management:** in addition to customer and service intent there are also other business requirements to comply with local rules, e.g., EMF emissions in wireless networks. These would be fed into the business layer and implemented within the wireless autonomous domain.
-
-**Network matching:** This provides the capability of locating the appropriate resource instances with which to deliver the network intent.
-
-## 3.5 Using the AN Framework
-
-# 5G Ride On! using the AN Framework
-
-![Diagram illustrating the 5G Ride On! 2020 Catalyst using the AN Framework. The diagram shows a multi-layered architecture. At the top, 'Business Operations' and 'Cross Domain Service Operations' are connected by a 'Cognitive Loop'. Below these are three domains: 'Fixed / Wireless', 'Transport', and 'Central / Edge Core', each containing 'NE' (Network Elements). The diagram also shows 'Business Curator' and 'Service Intent SLA / SLO' on the left, and 'Resilient EV Charging' and 'Reliable Connectivity' on the right. A 'Cognitive Loop' is shown on the right side, connecting the domains. The diagram is titled 'Solving for Business Continuity'.](36117e9cb27c58484cd8d3e5f9dc7ac3_img.jpg)
-
-The diagram illustrates the 5G Ride On! 2020 Catalyst using the AN Framework. It shows a multi-layered architecture. At the top, 'Business Operations' and 'Cross Domain Service Operations' are connected by a 'Cognitive Loop'. Below these are three domains: 'Fixed / Wireless', 'Transport', and 'Central / Edge Core', each containing 'NE' (Network Elements). The diagram also shows 'Business Curator' and 'Service Intent SLA / SLO' on the left, and 'Resilient EV Charging' and 'Reliable Connectivity' on the right. A 'Cognitive Loop' is shown on the right side, connecting the domains. The diagram is titled 'Solving for Business Continuity'.
-
-Diagram illustrating the 5G Ride On! 2020 Catalyst using the AN Framework. The diagram shows a multi-layered architecture. At the top, 'Business Operations' and 'Cross Domain Service Operations' are connected by a 'Cognitive Loop'. Below these are three domains: 'Fixed / Wireless', 'Transport', and 'Central / Edge Core', each containing 'NE' (Network Elements). The diagram also shows 'Business Curator' and 'Service Intent SLA / SLO' on the left, and 'Resilient EV Charging' and 'Reliable Connectivity' on the right. A 'Cognitive Loop' is shown on the right side, connecting the domains. The diagram is titled 'Solving for Business Continuity'.
-
-Figure 3-2 5G Ride On! 2020 Catalyst using AN Framework
-
-Figure 3-2 shows how the AN framework can be applied to a specific business objective, namely business continuity. The need for resilience connectivity to provide reliable services was the key focus. The Charge Point Operators as CSP customer is connected to the network using cross-layer customer loop. The vendors provided the system platforms that realized Self-X capabilities and closed loops required. The network is organized into three separate autonomous domains, namely Access, Transport, and Edge-Core. Self-healing and Self-protection within Fixed and Wireless access using 5G, with MEC orchestration and MEC offloading for self-optimization in the Edge Domain.
-
-# 4 Use Cases using AN Level Evaluation Methodology
-
-This section now describes two use case examples that apply the AN Level evaluation methodology described in IG1230.
-
-## 4.1 Level Evaluation for IPRAN Assurance
-
-This section selects the monitoring and troubleshooting of the IPRAN network of mobile 2C service as an example to describe the Autonomous Network Level. The monitoring and troubleshooting process is one of the most important processes in CSP network O&M. The full autonomy of the monitoring and troubleshooting process can reduce the workload of personnel and lower the skill requirements for O&M personnel, the troubleshooting duration can be shortened to improve end-user experience. Operation process and operation tasks for the IPRAN network of mobile 2C service are divided into the monitoring and troubleshooting operation process into nine operation tasks.
-
-**Task A: Intent Translation.** Based on the monitoring and assurance requirements and SLA assurance policies, determine network monitoring rules, such as the monitored area, monitored object (such as NEs or services), alarm type, alarm severity, KPI type, and alarm reporting policy for KPI exceptions. The system monitors the network based on the network monitoring rules.
-
-**Task B: Fault identification.** Monitors and analyzes network operation data and external data to detect unexpected service interruptions or service quality deterioration promptly.
-
-**Task C: Potential Risk Prediction.** Monitors and analyzes network operation data and external data, predicts the trend of network software and hardware status, and detects potential exceptions in advance.
-
-**Task D: Problem Demarcation.** Demarcate faults based on the identified faults and potential risks. In the cross-domain scenario, demarcate the fault to a specific technical domain. In the single-domain scenario, demarcate the fault to a specific NE.
-
-**Task E: Root cause location.** Based on the problem demarcation result, further locate the specific software and hardware causes (such as configurations, boards, and optical modules) of the problem to support the generation of rectification solutions and rectify services as soon as possible.
-
-**Task F: Recovery solution generation.** Based on the fault demarcation and locating results, generate several alternative recovery solutions, such as modifying configurations, restarting NEs, replacing boards, and isolating NEs.
-
-**Task G: Solution evaluation and decision-making.** Evaluate the repair solution (such as whether the solution can solve the problem, whether the repair cost is acceptable, and the extra impact on the network), and provide the optimal solution.
-
-**Task H: Recovery solution implementation.** Recovery faults and eliminate potential risks based on the optimal solution. For example, deliver configurations to the network for software faults, isolate NEs or links for hardware faults, or replace or remove boards or optical modules onsite.
-
-**Task I: Service verification.** After fault recovery and risk elimination are performed, verify and confirm the execution results, such as whether service interruption, quality deterioration, and alarms and KPI exceptions are cleared.
-
-### 6.1.1 Task Criteria for monitoring and troubleshooting of IPRAN network of mobile 2C services
-
-Each task can be completed manually by a human operator, or jointly by the operator and the system, or fully automatically by the system. The following table lists the monitoring and troubleshooting autonomous level standards based on the division of Manual and system:
-
-**Table 2 Level Evaluation for monitoring and troubleshooting of IPRAN**
-
-| AI-based cognitive workflow | Task                                            | L0                       | L1                   | L2                   | L3                   | L4                   | L5                  |
-|-----------------------------|-------------------------------------------------|--------------------------|----------------------|----------------------|----------------------|----------------------|---------------------|
-| Intent                      | Task A: Intent Translation                      | Person                   | Person               | System assist person | System assist person | Person assist system | System              |
-| Awareness                   | Task B: Fault identification                    | Person                   | System assist person | Person assist system | System               | System               | System              |
-|                             | Task C: Potential Risk Prediction               | Person                   | Person               | System assist person | Person assist system | System               | System              |
-| Analysis                    | Task D: Problem Demarcation                     | Person                   | System assist person | Person assist system | System               | System               | System              |
-|                             | Task E: Root cause location I                   | Person                   | System assist person | Person assist system | Person assist system | System               | System              |
-| Decision                    | Task F: Recovery solution generation            | Person                   | Person               | System assist person | Person assist system | System               | System              |
-|                             | Task G: Solution evaluation and decision-making | Person                   | Person               | System assist person | Person assist system | System               | System              |
-| Execution                   | Task H: Recovery solution implementation        | Person                   | System assist person | System               | System               | System               | System              |
-|                             | Task I: Service verification                    | Person                   | System assist person | Person assist system | System               | System               | System              |
-| Scenario applicability      |                                                 | Selected Fault Scenarios |                      |                      |                      |                      | All Fault Scenarios |
-
-Level0: All monitoring and troubleshooting tasks are manually completed.
-
-Level1: Problem identification (Task B), Problem Demarcation (Task D), Root cause analysis (Task E), recovery solution implementation (Task H), and Services verification (Task I) are completed by manual and systems (for example, automatic data collection and manual fault identification).
-
-Level2: Based on level 1, Recovery solution implementation (Task H) can be completed automatically by the system.
-
-Level3: Problem identification (Task B), Problem Demarcation (Task D), recovery solution implementation (Task H), and service verification (Task I) can be automatically completed by the system.
-
-Level4: All other tasks except Intent Translation (Task A) are automated.
-
-Level5: All tasks are automatically completed by the system.
-
-### 4.1.2 Evaluation Method
-
-The evaluation procedure is as follows:
-
-- 1) *Determine the evaluation object.*
-
-Defined Evaluation Object from service, network, operation process. In this example, select Mobile 2C Service, IPRAN network, Monitoring Troubleshooting operation process as an evaluation object.
-
-- 2) *Describes the evaluation object operation process and sub=process*
-- 3) *Map to operational tasks and evaluate autonomous level of tasks*
-
-Evaluate the level of each task based on the task criteria and automation capabilities in practice.
-
-**Table 3 Level Evaluation for monitoring and troubleshooting of IPRAN network**
-
-| AI-based cognitive workflow | Task                                            | L0                       | L1                   | L2                   | L3                   | L4                   | L5                  |
-|-----------------------------|-------------------------------------------------|--------------------------|----------------------|----------------------|----------------------|----------------------|---------------------|
-| Intent                      | Task A: Intent Translation                      | Person                   | Person               | System assist person | System assist person | Person assist system | System              |
-| Awareness                   | Task B: Fault identification                    | Person                   | System assist person | Person assist system | System               | System               | System              |
-|                             | Task C: Potential Risk Prediction               | Person                   | Person               | System assist person | Person assist system | System               | System              |
-| Analysis                    | Task D: Problem Demarcation                     | Person                   | System assist person | Person assist system | System               | System               | System              |
-|                             | Task E: Root cause location I                   | Person                   | System assist person | Person assist system | Person assist system | System               | System              |
-| Decision                    | Task F: Recovery solution generation            | Person                   | Person               | System assist person | Person assist system | System               | System              |
-|                             | Task G: Solution evaluation and decision-making | Person                   | Person               | System assist person | Person assist system | System               | System              |
-| Execution                   | Task H: Recovery solution implementation        | Person                   | System assist person | System               | System               | System               | System              |
-|                             | Task I: Service verification                    | Person                   | System assist person | Person assist system | System               | System               | System              |
-| Scenario applicability      |                                                 | Selected Fault Scenarios |                      |                      |                      |                      | All Fault Scenarios |
-
-For example, the red box indicates the task assessment of the current situation.
-
-**Table 4 Evaluate the level of each task for monitoring and troubleshooting**
-
-| Operation action of task                      | Task                              | AN Level of tasks |
-|-----------------------------------------------|-----------------------------------|-------------------|
-| design alarm handling rules and policies      | Task A: Intent Translation        | 1                 |
-| Alarm generate, filter, and report            | Task B: Fault identification      | 4                 |
-| Alarm parse, standardize, and alarm associate |                                   |                   |
-| None                                          | Task C: Potential Risk Prediction | 1                 |
-
-| Operation action of task                                 | Task                                            | AN Level of tasks |
-|----------------------------------------------------------|-------------------------------------------------|-------------------|
-| Problem analysis (demarcating NEs, boards, and ports)    | Task D: Problem Demarcation                     | 4                 |
-| Fault analysis (for example, power failure or fiber cut) | Task E: Root cause Location                     | 3                 |
-| Design recovery solution.                                | Task F: Recovery Solution generation            | 1                 |
-| Recovery Solution Select                                 | Task G: Solution evaluation and decision-making | 1                 |
-| Fault rectification                                      | Task H: Recovery solution implementation        | 1                 |
-| Confirm the Repair Result                                |                                                 |                   |
-| Service test verification                                | Task I: Service verification                    | 1                 |
-
-### 4.1.3 Example of evaluation object AN level
-
-In step 3, the task level is evaluated. Based on the average method, the autonomous level of the monitoring and troubleshooting of the IPRAN network of mobile 2C service is 1.9. The Problem identification task and Problem Demarcation task are highly automated. The system collects network alarm, performance, and topology data and automatically aggregates and analyzes the data to accurately identify and demarcate problems.
-
-## 4.2 Level Evaluation for HBB Intelligent O&M
-
-This section selects Monitoring and troubleshooting of the Home & Access & Metro network for home broadband service (HBB O&M) as an example to describe the Autonomous Network Level. The HBB O&M analysis, task description, task capability criteria, etc. are for reference, and some need to be further researched.
-
-Home broadband (HBB) maintenance is to ensure the voice, Internet, video services, etc., which are carried by the HBB network, it involves fault reporting, network monitoring, network fault handling, network risk check, and potential risk elimination, etc. The following shows the requirement architecture of home broadband O&M.
-
-Network-based complaints rising generally go through three phases: Network Risk/Degradation, Network fault, and User complaint. Customers' requirements and network maintenance focus vary across those phases.
-
-![Figure 4-1: Home broadband O&M requirements architecture. This diagram shows a multi-layered architecture. The top layer (Customer) includes 'User complaints prediction and prevention' and 'User complaint intelligent diagnosis'. The middle layer (Service) includes 'Proactive Faults Prediction and Prevention', 'Massive Faults Interception', and 'Network Faults Intelligent Diagnosis'. The bottom layer (Resource) includes 'PM' and 'FM'. A central flow shows three phases: 'Network Risk /Degradation' (yellow), 'Network Fault' (orange), and 'User Complaint' (red), leading to 'Restoration'. Below these phases are event triggers: 'Risk, Degradation events', 'Fault events', and 'Complaint events'. A large green arrow on the right indicates the flow towards restoration.](d53cd0fd1cf896a9353fd63de1505ba2_img.jpg)
-
-Figure 4-1: Home broadband O&M requirements architecture. This diagram shows a multi-layered architecture. The top layer (Customer) includes 'User complaints prediction and prevention' and 'User complaint intelligent diagnosis'. The middle layer (Service) includes 'Proactive Faults Prediction and Prevention', 'Massive Faults Interception', and 'Network Faults Intelligent Diagnosis'. The bottom layer (Resource) includes 'PM' and 'FM'. A central flow shows three phases: 'Network Risk /Degradation' (yellow), 'Network Fault' (orange), and 'User Complaint' (red), leading to 'Restoration'. Below these phases are event triggers: 'Risk, Degradation events', 'Fault events', and 'Complaint events'. A large green arrow on the right indicates the flow towards restoration.
-
-Figure 4-1 Home broadband O&amp;M requirements architecture
-
-### 4.2.1 Operation process and operation tasks
-
-Base on the 3 phases and service layer described above, there are 3 user cases: Proactive Faults Prediction and Prevention, Massive fault interception, and Network fault intelligent diagnosis.
-
-![Figure 4-2: Operational processes home broadband O&M use cases. This diagram illustrates three use cases (UC1, UC2, UC3) across four roles: User, Call Center, NOC/SOC, and FME. UC3 (Network Faults Intelligent Diagnosis) shows a flow from User complain to Call Center (Self-diagnosis & Restoration), then to NOC/SOC (Expert diagnosis & Restoration), and finally to FME (Auto-Dispatch and On-site work & Restoration). UC2 (Massive Faults Interception) shows a flow from Network monitoring to NOC/SOC (Auto-Diagnosis & Restoration), then to FME (Auto-Dispatch and On-site work & Restoration). UC1 (Proactive Faults Prediction and Prevention) shows a flow from User service status monitoring and Network risk analysis to NOC/SOC (Auto-Diagnosis & Restoration), then to FME (Auto-Dispatch and On-site work & Restoration).](5793a44ffdadd039928e2f9fe6daae06_img.jpg)
-
-Figure 4-2: Operational processes home broadband O&M use cases. This diagram illustrates three use cases (UC1, UC2, UC3) across four roles: User, Call Center, NOC/SOC, and FME. UC3 (Network Faults Intelligent Diagnosis) shows a flow from User complain to Call Center (Self-diagnosis & Restoration), then to NOC/SOC (Expert diagnosis & Restoration), and finally to FME (Auto-Dispatch and On-site work & Restoration). UC2 (Massive Faults Interception) shows a flow from Network monitoring to NOC/SOC (Auto-Diagnosis & Restoration), then to FME (Auto-Dispatch and On-site work & Restoration). UC1 (Proactive Faults Prediction and Prevention) shows a flow from User service status monitoring and Network risk analysis to NOC/SOC (Auto-Diagnosis & Restoration), then to FME (Auto-Dispatch and On-site work & Restoration).
-
-Figure 4-2 Operational processes home broadband O&amp;M use cases
-
-We take UC1 to describe the evaluation method in detail.
-
-Note: UC1 focuses on phase 1 based on Figure - Home broadband O&M requirements architecture, so there is no task - Fault identification in "Awareness".
-
-![Figure 4-3: Fault Prediction and Prevention workflow diagram. The workflow is a closed loop involving the Operator/Customer and the HBB Network. The Operator/Customer sends an 'Intent' to 'Intent translation' (Task A: Intention Translation). This leads to 'Awareness' (Task B: Fault Identification, Task C: Potential Risk Prediction) via an 'Operation Rule'. 'Awareness' sends an 'Event report' to 'Analysis' (Task D: Problem Demarcation, Task E: Root cause Location). 'Analysis' sends an 'Analysis result' to 'Decision' (Task F: Recovery Solution Generation, Task G: Solution evaluation and Decision-making). 'Decision' sends a 'Restoration strategy' to 'Execution' (Task H: Recovery solution Implementation, Task I: Service Verification). 'Execution' sends a 'Strategy: command, script, etc.' back to the HBB Network. The HBB Network sends 'Data: alarm, performance, log, etc.' back to 'Awareness'. Finally, 'Execution' sends a 'Restoration result / Service status' back to the Operator/Customer, which also feeds back into 'Intent translation'.](d734a6ea1b381280f043fcf70391b6db_img.jpg)
-
-Figure 4-3: Fault Prediction and Prevention workflow diagram. The workflow is a closed loop involving the Operator/Customer and the HBB Network. The Operator/Customer sends an 'Intent' to 'Intent translation' (Task A: Intention Translation). This leads to 'Awareness' (Task B: Fault Identification, Task C: Potential Risk Prediction) via an 'Operation Rule'. 'Awareness' sends an 'Event report' to 'Analysis' (Task D: Problem Demarcation, Task E: Root cause Location). 'Analysis' sends an 'Analysis result' to 'Decision' (Task F: Recovery Solution Generation, Task G: Solution evaluation and Decision-making). 'Decision' sends a 'Restoration strategy' to 'Execution' (Task H: Recovery solution Implementation, Task I: Service Verification). 'Execution' sends a 'Strategy: command, script, etc.' back to the HBB Network. The HBB Network sends 'Data: alarm, performance, log, etc.' back to 'Awareness'. Finally, 'Execution' sends a 'Restoration result / Service status' back to the Operator/Customer, which also feeds back into 'Intent translation'.
-
-Figure 4-3 Fault Prediction and Prevention workflow
-
-The workflow of proactive faults prediction and prevention use case begins with operation intent. The system receives operation intent from the human operator and translates it into operational rules. These rules specify how the system runs to achieve the goal of operation intent. And the system organizes serial tasks to implement the operation rules. Typically, the tasks can be classified into 4 types: *Awareness*, *Analysis*, *Decision*, and *Execution* as shown in Figure 4-3. The tasks form a closed control loop with network devices to continuously ensure the achievement of operation intent. The tasks of this use case are listed as follows:
-
-Table 5 Task of UC1-“HBB Fault Prediction and Prevention”
-
-| Task   | Name                      | Function description for UC1                                                                                                                                                                                                                                                                                                                                                                                                                                          |
-|--------|---------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| Task A | Intention Translation     | Based on the monitoring and assurance requirements and SLA assurance policies, determine network monitoring rules, such as the monitored area, monitored object (such as NEs or services), alarm type, alarm severity, KPI type, and alarm reporting policy for KPI exceptions. The system monitors the network based on the network monitoring rules.                                                                                                                |
-| Task B | Fault Identification      | Not Applicable. This UC is for phase 1 which before network fault rising based on the Figure - Home broadband O&M requirements architecture.                                                                                                                                                                                                                                                                                                                          |
-| Task C | Potential risk Prediction | Detection and data collection: Detects network and home broadband service risks and degradations, and collects related data, such as alarms, performance, configurations, logs, and STB probes.<br>Potential risk identification: Predicts the trend of network software and hardware status and identifies the potential risk of HBB service.<br>Exception event filtering: Removes noises. For example, filter out abnormal events caused by normal user behaviors. |
-| Task D | Problem Demarcation       | Demarcate the risk and degradation event to a specific technical domain, for HBB network should be Terminals, Home network, Access network, Metro network, CDN network.                                                                                                                                                                                                                                                                                               |
-| Task E | Root cause Location       | Based on the problem demarcation result, further locate the specific software and hardware causes (such as configurations, boards, and optical modules) of the problem to support the generation of recovery solutions.                                                                                                                                                                                                                                               |
-
-| Task   | Name                                    | Function description for UC1                                                                                                                                                                                         |
-|--------|-----------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| Task F | Recovery Solution Generation            | Based on the root causes analysis result, output a feasible recovery solution. Multiple recovery solutions are available, such as remote configuration modification, remote reset, and onsite component replacement. |
-| Task G | Solution evaluation and Decision-making | Evaluate the repair solution (such as whether the solution can solve the problem, whether the repair cost is acceptable, and the extra impact on the network), and provide the optimal solution.                     |
-| Task H | Recovery solution Implementation        | Implement the recovery solution to eliminate potential network risks. For operations that cannot be automatically rectified by the system, manual rectification is needed.                                           |
-| Task I | Service Verification                    | After the solution is performed, verify and confirm the execution results, such as whether service interruption, quality deterioration, and alarms and KPI exceptions are cleared.                                   |
-
-### 4.2.2 Metrics and Capabilities criteria
-
-![Diagram showing the relationship between Service KPI, UseCase, and Technical KPI.](4b87467ad9642943235f48f7d4b59449_img.jpg)
-
-The diagram illustrates the relationship between three levels of metrics and capabilities:
-
-- Service KPI:** Includes four orange boxes: "User complaint rate", "Site/Door visit rate", "MTTR", and "FCR".
-- UseCase:** A dashed blue box containing three green boxes: "Proactive Faults Prediction and Prevention", "Massive Faults Interception", and "Network Faults Intelligent Diagnosis".
-- Technical KPI:** A blue box labeled "TBD (For example, Scenario coverage rate, Identification granularity, Automation rate, etc.)".
-
-Connections:
-
-- Blue lines connect each Service KPI box to each UseCase box, indicating a many-to-many relationship.
-- A double-headed blue arrow connects the UseCase box to the Technical KPI box, indicating a bidirectional relationship.
-
-Diagram showing the relationship between Service KPI, UseCase, and Technical KPI.
-
-Figure 4-4 Relationship between service KPI, use cases, and technical KPI
-
-**Service KPI:** Used by most CSP to measure the performance of home broadband O&M. It is not only related to technical KPI but also related to the customer's organization, manpower, and network resource performance, etc.
-
-**Technical KPI:** To support service KPI, some technical indicators reflect the system capability, we named them Technical KPI. It is the system specifications that dictate the maximum capability of the system under certain conditions. For example, Scenario coverage rate, Identification granularity (like network/port level, service level, application-level), Automation rate, etc. It needs to be further researched.
-
-Capabilities criteria based on task for AN level of HBB Proactive Faults Prediction and Prevention is as below in Table 6 Task level evaluation reference criteria for AN level of "HBB Proactive Faults Prediction and Prevention".
-
-Table 6 Task level evaluation reference criteria for AN level of “HBB Proactive Faults Prediction and Prevention”
-
-| Cognitive Workflow     | Task                                           | L0                 | L1                  | L2                  | L3                  | L4                  | L5            |
-|------------------------|------------------------------------------------|--------------------|---------------------|---------------------|---------------------|---------------------|---------------|
-| Intent                 | Task A:Intent Translation                      | Person             | Person              | System assit person | System assit person | Person assit system | System        |
-| Awareness              | Task B:Fault Identification                    | N/A                | N/A                 | N/A                 | N/A                 | N/A                 | N/A           |
-|                        | Task C: Potential risk Prediction              | Person             | Person              | System assit person | Person assit system | System              | System        |
-| Analysis               | Task D:Problem Demarcation                     | Person             | System assit person | Person assit system | System              | System              | System        |
-|                        | Task E:Root cause Location                     | Person             | System assit person | Person assit system | Person assit system | System              | System        |
-| Decision               | Task F:Recovery solution Generation            | Person             | System assit person | Person assit system | System              | System              | System        |
-|                        | Task G:Solution evaluation and Decision-making | Person             | Person              | System assit person | Person assit system | System              | System        |
-| Execution              | Task H: Recovery solution Implementation       | Person             | System assit person | System              | System              | System              | System        |
-|                        | Task I:Service Verification                    | Person             | System assit person | Person assit system | Person assit system | System              | System        |
-| Scenario applicability |                                                | Selected Scenarios |                     |                     |                     |                     | All Scenarios |
-
-### 4.2.3 Evaluation Method
-
-Evaluate the level of each task based on the task criteria above and automation capabilities in practice. Based on the average method, calculate the AN level of “HBB Proactive Faults Prediction and Prevention”.
-
-# 5. Administrative
-
-## 5.1 Document History
-
-### 5.1.1 Version History
-
-| Version Number | Date Modified | Modified by:                        | Description of changes         |
-|----------------|---------------|-------------------------------------|--------------------------------|
-| 0.1            | 20-Aug-2020   | Kevin McDonnell                     | Initial Draft.                 |
-| 0.24           | 18-Sep-2020   | James O'Sullivan<br>Kevin McDonnell | Use Cases from Catalysts added |
-| 0.36           | 04-Oct 2020   | Kevin McDonnell                     | Final draft for team review    |
-| 1.0.0          | 23-Nov 2020   | Alan Pope                           | Final edits before publication |
-| 1.0.1          | 28-Apr-2021   | Kevin McDonnell                     | IG1230A Guide draft            |
-| 1.1.0          | 28-May-2021   | Alan Pope                           | Final edits before publication |
-
-### 5.1.2 Release History
-
-| Release Status | Date Modified | Modified by:     | Description of changes                      |
-|----------------|---------------|------------------|---------------------------------------------|
-| Pre-production | 25th May 2021 | Kevin McDonnell  | IG1230A Guide Team Approved                 |
-| Production     | 26-Jul-2021   | Adrienne Walcott | Updated to reflect TM Forum Approved Status |
-
-## 5.2 Acknowledgments
-
-This document was prepared by members of the TM Forum Autonomous Networks project.
-
-### 5.2.1 Guide Lead & Author
-
-| Member          | Title                                   | Company |
-|-----------------|-----------------------------------------|---------|
-| Kevin McDonnell | Senior Director, Intelligent Automation | Huawei  |
-
-### 5.2.2 Main Contributors
-
-| Member           | Title                                    | Company           |
-|------------------|------------------------------------------|-------------------|
-| James O'Sullivan | Product Director, Intelligent Automation | Huawei            |
-| Yuval Stein      | AVP Technologies                         | TEOCO corporation |
-| Wang Lei         | Systems Expert                           | Huawei            |
-| Wang Xu          | Systems Expert                           | Huawei            |
-
-### **5.2.3 Additional Inputs**
-
-| Member              | Title                                                          | Company                |
-|---------------------|----------------------------------------------------------------|------------------------|
-| Abdul Majid Hussain | Solutions Architect                                            | Telstra                |
-| Abinash Vishwakarma | Lead Business Analyst                                          | Netcracker             |
-| Andy Corston-Petrie | Senior Research Manager                                        | BT Group plc           |
-| Brad Peters         | Architect                                                      | NBNCo Ltd              |
-| Christian Maître    | VP Smart Territories                                           | Orange                 |
-| Dong Sun            | Chief Business Strategist, Digital Transformation              | Futurewei Technologies |
-| Emmanuel A. Otchere | Chief Technical Expert<br>VP, Standards & Industry Development | Huawei                 |
-| Joe Isaac           | Principal Architect                                            | Wipro Technologies     |
-| Johanne Mayer       | Consultant                                                     | Ciena                  |
-| Liu Hongbo          | Deputy General Manager, Intelligent Network Center             | China Unicom           |
-| Luigi Licciardi     | Consultant, Executive Advisor                                  | Huawei                 |
-| Manoj Nair          | Senior Solutions Architect, CTO Office                         | Netcracker             |
-| Min He              | Chief Architect                                                | Futurewei Technologies |
-| Qiao Zizhi          | Senior Engineer, Intelligent Network Center                    | China Unicom           |
-| Steve Iatropoulos   | Client & Industry CTO                                          | Microsoft              |
-| Tayeb Ben Meriem    | Senior Standardization Manager                                 | Orange                 |
-| Thierry Reynard     | OSS Consulting Manager                                         | ETIYA                  |
-| Vance Shipley       | CEO                                                            | Sigscale               |
-| Xie Yuan            | Systems Expert                                                 | Huawei                 |
-| Zheng Guangying     | Systems Expert                                                 | Huawei                 |
-
-### **5.2.4 TM Forum Staff**
-
-| TM Forum            | Title                                          | Company  |
-|---------------------|------------------------------------------------|----------|
-| Aaron Boasman-Patel | Vice President, AI, Customer Experience & Data | TM Forum |
-| Alan Pope           | Collaboration Manager                          | TM Forum |
-| David Milham        | Chief Architect                                | TM Forum |
-| Ian Turkington      | VP, Architecture & APIs                        | TM Forum |
-| W. George Glass     | CTO                                            | TM Forum |

marked/Autonomous_Networks/IG1230B_Autonomous_Networks_Industry_Standards_v1.1.0/raw.md

@@ -1,346 +0,0 @@
-
-
-# TM Forum Introductory Guide
-
-## Autonomous Networks Industry Standards
-
-**IG1230B**
-
-**Team Approval Date : 28-May-2021**
-
-|                                   |                                           |
-|-----------------------------------|-------------------------------------------|
-| <b>Release Status: Production</b> | <b>Approval Status: TM Forum Approved</b> |
-| <b>Version 1.1.0</b>              | <b>IPR Mode: RAND</b>                     |
-
-## Notice
-
-Copyright © TM Forum 2021. All Rights Reserved.
-
-This document and translations of it may be copied and furnished to others, and derivative works that comment on or otherwise explain it or assist in its implementation may be prepared, copied, published, and distributed, in whole or in part, without restriction of any kind, provided that the above copyright notice and this section are included on all such copies and derivative works. However, this document itself may not be modified in any way, including by removing the copyright notice or references to TM FORUM, except as needed for the purpose of developing any document or deliverable produced by a TM FORUM Collaboration Project Team (in which case the rules applicable to copyrights, as set forth in the [TM FORUM IPR Policy](#), must be followed) or as required to translate it into languages other than English.
-
-The limited permissions granted above are perpetual and will not be revoked by TM FORUM or its successors or assigns.
-
-This document and the information contained herein is provided on an “AS IS” basis and TM FORUM DISCLAIMS ALL WARRANTIES, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF THE INFORMATION HEREIN WILL NOT INFRINGE ANY OWNERSHIP RIGHTS OR ANY IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.
-
-TM FORUM invites any TM FORUM Member or any other party that believes it has patent claims that would necessarily be infringed by implementations of this TM Forum Standards Final Deliverable, to notify the TM FORUM Team Administrator and provide an indication of its willingness to grant patent licenses to such patent claims in a manner consistent with the IPR Mode of the TM FORUM Collaboration Project Team that produced this deliverable.
-
-The TM FORUM invites any party to contact the TM FORUM Team Administrator if it is aware of a claim of ownership of any patent claims that would necessarily be infringed by implementations of this TM FORUM Standards Final Deliverable by a patent holder that is not willing to provide a license to such patent claims in a manner consistent with the IPR Mode of the TM FORUM Collaboration Project Team that produced this TM FORUM Standards Final Deliverable. TM FORUM may include such claims on its website but disclaims any obligation to do so.
-
-TM FORUM takes no position regarding the validity or scope of any intellectual property or other rights that might be claimed to pertain to the implementation or use of the technology described in this TM FORUM Standards Final Deliverable or the extent to which any license under such rights might or might not be available; neither does it represent that it has made any effort to identify any such rights. Information on TM FORUM's procedures with respect to rights in any document or deliverable produced by a TM FORUM Collaboration Project Team can be found on the TM FORUM website. Copies of claims of rights made available for publication and any assurances of licenses to be made available, or the result of an attempt made to obtain a general license or permission for the use of such proprietary rights by implementers or users of this TM FORUM Standards Final Deliverable, can be obtained from the TM FORUM Team Administrator. TM FORUM makes no representation that any information or list of intellectual property rights will at any time be complete, or that any claims in such list are, in fact, Essential Claims.
-
-Direct inquiries to the TM Forum office:
-
-181 New Road, Suite 304  
-Parsippany, NJ 07054 USA  
-Tel No. +1 862 227 1648  
-TM Forum Web Page: [www.tmforum.org](http://www.tmforum.org)
-
-# Table of Contents
-
-|                                                                           |           |
-|---------------------------------------------------------------------------|-----------|
-| <b>Notice.....</b>                                                        | <b>2</b>  |
-| <b>Table of Contents .....</b>                                            | <b>4</b>  |
-| <b>List of Figures .....</b>                                              | <b>5</b>  |
-| <b>List of Tables.....</b>                                                | <b>6</b>  |
-| <b>1 Industry and Standardization Efforts .....</b>                       | <b>7</b>  |
-| 1.1 Towards a shared vision of Autonomous Networks .....                  | 7         |
-| 1.2 SDO Landscape Summary.....                                            | 7         |
-| 1.3 SDO Deliverables Summary.....                                         | 9         |
-| <b>2 SDO Landscape.....</b>                                               | <b>11</b> |
-| 2.1 European Telecommunications Standards Institute (ETSI) .....          | 11        |
-| 2.2 3rd Generation Partnership Project (3GPP) .....                       | 11        |
-| 2.3 International Telecommunication Union Telecommunication (ITU-T) ..... | 12        |
-| <b>3 Intent in Autonomous Networks .....</b>                              | <b>13</b> |
-| 3.1 Intent Standardization Efforts.....                                   | 13        |
-| <b>4 Administrative .....</b>                                             | <b>15</b> |
-| 4.1 References.....                                                       | 15        |
-| 4.2 Document History .....                                                | 16        |
-| 4.3 Acknowledgements.....                                                 | 16        |
-
-# List of Figures
-
-Figure 1. Industry and Standards Landscape..... 7
-
-Figure 2. ETSI ISGs relating to AN (Source: ETSI 2020) ..... 11
-
-Figure 3. Overview of ML work in FG ML5G [Y3172] (Callouts added)..... 12
-
-# List of Tables
-
-|                                                                  |    |
-|------------------------------------------------------------------|----|
-| <b>Table 1. SDO Projects or Specification Groups</b>             | 8  |
-| <b>Table 2. Review of ongoing AN activities in relevant SDOs</b> | 9  |
-| <b>Table 3. Intent Standards Classification</b>                  | 13 |
-
-# 1 Industry and Standardization Efforts
-
-## 1.1 Towards a shared vision of Autonomous Networks
-
-Autonomous Network initiatives are being progressed in multiple standards developing organizations (SDOs), such as ETSI, 3GPP, and GSMA to name but a few. An alignment on Autonomous Network concepts, a shared vision and framework would help the industry to progress in a coordinated way on this important initiative.
-
-Autonomous Networks evolution, standardization, and deployment will require an industry-wide consensus and each stakeholder will need to learn how to collaborate better to create the right approach. For standards work, SDOs will need to “share early and often”, align better and avoid duplication of effort.
-
-Autonomous Networks will evolve over a longer-term timeline and real solution deployments using AI that delivers a high level of network automation (AN Level 4) are expected in the next 5 years. However, it is the next 2 years that will prove crucial to its success. Concrete, tangible elements of the AN framework, generating the initial benefits and return, will deliver partially autonomous systems. These returns when reinvesting into the initiatives will bring bigger savings and the value behind AN. Standards should move fast to prepare the conditions of interoperability and commercial deployment of these autonomous systems.
-
-## 1.2 SDO Landscape Summary
-
-The challenges and opportunities of AN are significant, and no single stakeholder or SDO is capable to cover the entire end-to-end perspectives of AN. The cross-SDO, industry-level collaboration to achieve consensus of key concepts and terminologies (e.g., AN definition, framework, autonomous networks levels) and the development of key capabilities, mechanisms, interfaces (e.g., control loops, autonomous domains, intent) is essential to the success of AN.
-
-![Figure 1: Industry and Standards Landscape. A collection of logos for various standards developing organizations (SDOs) and industry groups. The logos are arranged in a grid-like fashion. Top row: 3GPP (A GLOBAL INITIATIVE), CCSA, ETSI, GSMA. Middle row: IEEE, IETF, ITU. Bottom row: ONAP (OPEN NETWORK AUTOMATION PLATFORM), ngmn (the engine of broadband wireless innovation), and tmforum.](48d61f7cf40bacce4d63f9e98ea225fb_img.jpg)
-
-Figure 1: Industry and Standards Landscape. A collection of logos for various standards developing organizations (SDOs) and industry groups. The logos are arranged in a grid-like fashion. Top row: 3GPP (A GLOBAL INITIATIVE), CCSA, ETSI, GSMA. Middle row: IEEE, IETF, ITU. Bottom row: ONAP (OPEN NETWORK AUTOMATION PLATFORM), ngmn (the engine of broadband wireless innovation), and tmforum.
-
-Figure 1. Industry and Standards Landscape
-
-Figure 1, Industry and Standards Landscape, shows a simplified <sup>4</sup>view of the key organizations that are active in the area of AN – from standards to open source implementations such as ONAP. The table below defines the objectives of this SDO projects and groups. Table 1 below lists the objectives of some relevant projects in AN space.
-
-Table 1. SDO Projects or Specification Groups
-
-| Project           | Objective                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
-|-------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| <b>ETSI ENI</b>   | Experiential Networked Intelligence Industry Specification Group (ENI ISG) is defining a Cognitive Network Management architecture, using Artificial Intelligence (AI) techniques and context-aware policies to adjust offered services based on changes in user needs, environmental conditions and business goals. ISGENI is focused on improving the experience of the operator in managing any type of network                                                                                                                                                 |
-| <b>ETSI GANA</b>  | The main goal of the GANA reference model is prescribing design and operational principles for Decision Elements (DEs) as the drivers for cognitive, self-managing and self-adaptive network behaviors that enable to achieve OPEX reduction and other benefits "Artificial Intelligence/Cognition in AMC (autonomics)" bring to Network Operators and End User Customers, and to Enterprise Networks as well, such as: Dynamic and Analytics-Driven Service Fulfilment and Closed-Loop Service Assurance, Predictive, Proactive and Advanced Customer Experience. |
-| <b>ETSI ZSM</b>   | Defines and describes the reference architecture for the end-to-end Zero-touch network and Service Management (ZSM) framework based on a set of user scenarios and requirements documented in ETSI GS ZSM 001. The overarching design goal of ZSM is to enable zero-touch automated network and service management in a multivendor environment.                                                                                                                                                                                                                   |
-| <b>ETSI F5G</b>   | The ETSI ISG F5G aims at studying the fixed-network evolution required to match and further enhance the benefits that 5G has brought to mobile networks and communications. It will define improvements with respect to previous solutions and the new characteristics of the fifth-generation fixed network.                                                                                                                                                                                                                                                      |
-| <b>ITU-T SG13</b> | Specifies an architectural framework for machine learning (ML) in future networks: a set of architectural requirements, specific architectural components needed to satisfy these requirements (components include, but are not limited to, a ML pipeline as well as ML management and orchestration functionalities), integration of such components into future networks and guidelines for applying this architectural framework in a variety of technology-specific underlying networks.                                                                       |
-| <b>3GPP SA5</b>   | Within the 3GPP Technical Specification Group Service and System Aspects (TSGSA), the main objectives of 3GPP TSG SA WG5 (SA5) are Management, Orchestration and Charging for 3GPP systems. Both functional and service perspectives are covered.                                                                                                                                                                                                                                                                                                                  |
-
-| Project          | Objective                                                                                                                                                                                                                                                                                                                                                                                                              |
-|------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| <b>IETF NMRG</b> | The Network Management Research Group (NMRG) provides a forum for researchers to explore new technologies for the management of the Internet. In particular, the NMRG will work on solutions for problems that are not yet considered well understood enough for engineering work within the IETF. The focus of the NMRG will be on management services that interface with the current Internet management framework. |
-| <b>CCSA TC7</b>  | TC7 is a technical committee supporting Network Management and Operation. WG1 focuses on Wireless communication management. WG2 focuses on Transport, Bearer, and Access Network Management. WG3 focuses on ICT Service Management and Operation.                                                                                                                                                                      |
-
-<sup>1</sup> It is not an exhaustive list of all SDOs in AN
-
-## 1.3 SDO Deliverables Summary
-
-Table 2 gives an overview of the objectives and published deliverables for the respective SDOs.
-
-Table 2. Review of ongoing AN activities in relevant SDOs
-
-| SDO      | Objectives                                                                                                                                                           | Planned Deliverables                                                                                                                                                                                                       | Published Deliverables                                                                                                                         |
-|----------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------|
-| TM Forum | E2E perspective<br>User stories<br>Business requirements/Business architecture<br>Technical architecture<br>Catalysts / PoCs                                         | IG1260 AN Project Guide<br>IG1251 (ANF Reference Architecture)<br>IG1252 (AN Levels Evaluation Methodology)<br>IG1253 Intent in Autonomous Networks<br>IG1259 Study of Telecom Industry Intent<br>Meta-Modeling Approaches | AN Whitepapers R19 and R20<br>IG1193 (Vision & Roadmap)<br>IG1218 (BA 1.0)<br>IG1229 (Guiding Principles)<br>IG1230 (TA 1.0)                   |
-| 3GPP SA5 | Autonomous Network levels<br>5G Service-Level Agreement<br>Closed loop assurance<br>Intent-driven management<br>Self-organizing network<br>Management data analytics | Autonomous Network levels:<br>TS 28.100<br>Intent-driven management:<br>TS 28.312<br>1. Management data analytics:<br>TS 28.104                                                                                            | Architecture: TS 28.533<br>closed loop automation: TS 28.535/536<br>Self-organizing network: TS 28.313<br>5G Service-Level Agreement TS 28.541 |
-
-| SDO       |       | Objectives                                                                                                | Planned Deliverables                                                                                                                                                                                                                                                            | Published Deliverables                                            |
-|-----------|-------|-----------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------|
-| ETSI      | ZSM   | Closed loop of Network operations automation; Cross-domain E2E Service LCM; Intent-driven AN; AI Enablers | GS ZSM 009-1 Closed-loop automation; Enablers.<br>GS ZSM 009-2 Closed-loop automation; Solutions<br>GS ZSM 009-3 Closed-loop automation; Advanced topics<br>. GS ZSM 008 Cross-domain E2E service LCM<br>GS ZSM 011 Intent-driven autonomous networks<br>GS ZSM 012 AI Enablers | ZSM002 v1.1.1<br>ZSM004 v1.1.1<br>ZSM005 v1.1.1.                  |
-|           | ENI   | Closed loop of AI for Network operations automation                                                       | Rel 2                                                                                                                                                                                                                                                                           | Rel 1 on Use cases, architecture, Context-Aware Policy Management |
-|           | F5G   | transport networks with AN capabilities                                                                   |                                                                                                                                                                                                                                                                                 |                                                                   |
-| GSMA      |       | Future Networks; Automation in Network evolution.                                                         |                                                                                                                                                                                                                                                                                 | Whitepaper: AI & Automation: An Overview                          |
-| ITU-T     | SG13  | Machine learning in future network                                                                        |                                                                                                                                                                                                                                                                                 | Y.3170-Y.3179                                                     |
-|           | FG-AN | Initial proposal on study of AN is now a new focus group called FG-AN (Feb 2021)                          |                                                                                                                                                                                                                                                                                 |                                                                   |
-| CCSA TC7  |       | Network Management and Operation                                                                          |                                                                                                                                                                                                                                                                                 |                                                                   |
-| IETF NMRG |       | Concepts; Intent classification; Service assurance; policy                                                | draft-irtf-nmrg-ibn-concepts-definitions-03<br>draft-irtf-nmrg-ibn-intent-classification-03<br>draft-zhou-nmrg-digitaltwin-network-concepts-03<br>draft-claise-opsawg-service-assurance-architecture-03<br>draft-ietf-netmod-eca-policy-01                                      | RFC7575, RFC7576                                                  |
-
-# 2 SDO Landscape
-
-The following sub-sections list some of the *recent* contributions to the AN topic from various SDO organizations.
-
-## 2.1 European Telecommunications Standards Institute (ETSI)
-
-ETSI have a number of standards activities relating to Autonomous Networks:
-
-- *F5G (5<sup>th</sup> Generation Fixed Network)*,
-- *ENI (Improve operator Experience through closed loop AI)*,
-- *NFV (Network Function Virtualization)*,
-- *ZSM (Management/Automation of emerging and future networks and services)*.
-
-![A diagram titled 'Simplistic Mapping of ETSI Activities' showing the flow of data and intent across four autonomous domains (A, B, C, D). Domain A (Access) includes Applications, Data collection, and Customers devices. Domain B (Edge/Aggregation) includes Applications and services, Data processing & governance agent, and Resources operations. Domain C (Transport) includes Applications and services. Domain D (Core & Cloud) includes Applications, Data analytics/Decision and Governance, and Business and Services Ops. Arrows indicate Data flow and various intents (Resource, Business, Service). Below the domains, ETSI ISGs are mapped: ISG F5G for Domain A, ISG MEC for Domain B, ISG NFV and OSG MANO for Domain C, and ISG ENI and ISG ZSM for Domain D. A dashed box at the bottom includes ISG SAI, TC CYBER, ISG PDL, and others.](8e14350b4b669119a3bdfca7869110ca_img.jpg)
-
-**‘Simplistic’ Mapping of ETSI Activities, (NOTE: all consider ‘end to end’)**
-
-The diagram illustrates the mapping of ETSI ISGs across four autonomous domains (A, B, C, D) in a network architecture. Domain A (Access) involves Applications, Data collection, and Customers devices. Domain B (Edge/Aggregation) involves Applications and services, Data processing & governance agent, and Resources operations. Domain C (Transport) involves Applications and services. Domain D (Core & Cloud) involves Applications, Data analytics/Decision and Governance, and Business and Services Ops. Arrows indicate Data flow and various intents (Resource, Business, Service). Below the domains, ETSI ISGs are mapped: ISG F5G for Domain A, ISG MEC for Domain B, ISG NFV and OSG MANO for Domain C, and ISG ENI and ISG ZSM for Domain D. A dashed box at the bottom includes ISG SAI, TC CYBER, ISG PDL, and others.
-
-A diagram titled 'Simplistic Mapping of ETSI Activities' showing the flow of data and intent across four autonomous domains (A, B, C, D). Domain A (Access) includes Applications, Data collection, and Customers devices. Domain B (Edge/Aggregation) includes Applications and services, Data processing & governance agent, and Resources operations. Domain C (Transport) includes Applications and services. Domain D (Core & Cloud) includes Applications, Data analytics/Decision and Governance, and Business and Services Ops. Arrows indicate Data flow and various intents (Resource, Business, Service). Below the domains, ETSI ISGs are mapped: ISG F5G for Domain A, ISG MEC for Domain B, ISG NFV and OSG MANO for Domain C, and ISG ENI and ISG ZSM for Domain D. A dashed box at the bottom includes ISG SAI, TC CYBER, ISG PDL, and others.
-
-**Figure 2. ETSI ISGs relating to AN (Source: ETSI 2020)**
-
-Figure 2 shows the ISGs working in areas related to autonomous networks and identifies areas of contribution and convergence of scope of the various ETSI ISGs. ETSI plans to publish a whitepaper on Autonomous Networks that shows the importance of coordination and knowledge sharing between the ISGs and all involved in the extended ecosystem, including SDOs, cross-vertical organizations, open-source alliances and research groups.
-
-## 2.2 3rd Generation Partnership Project (3GPP)
-
-3GPP SA5 has progressed the following specifications in the general area of AN:
-
-### *Architecture Framework*
-
-- In Release 16, 3GPP SA5 took the architectural framework specified in GS ZSM 002 (ZSM Reference Architecture) into account. The related description has been captured in TS 28.533 clause 5.3 “Management service deployment based on ZSM framework”.
-
-### Closed Loop Assurance
-
-- In 3GPP Release 16, 3GPP SA5 has specified the concept for open control loop and closed control loop, as well as use cases, requirements and a model for communication service assurance closed control loop. Corresponding contents are captured in TS 28.535 and TS 28.536.
-- In 3GPP Release 17, 3GPP SA5 has started a new work item on enhanced closed loop SLS assurance.
-
-### Classification of Network Autonomy for Fault recovery ( 28.810)
-
-In addition, SA5 is currently working on the following Rel-17 topics that are relevant to AN:
-
-- Intent driven management service for mobile networks (see TR 28.812/TS 28.312),
-- Management Data Analytics Service (see TR 28.809),
-- Autonomous Network Levels (see TR 28.810/TS 28.100).
-
-3GPP has also established the NWDAF (network data analytics function) working group to work on 5G slicing and intelligent application research of 5G Core.
-
-## 2.3 International Telecommunication Union Telecommunication (ITU-T)
-
-The ITU-T approved ITU-T Y.3172 in June 2019 to define the network AI framework, including the intelligence level, data processing standards, and cases. The Focus group on Machine Learning for Future Networks including 5G (FG-ML5G) has developed an Architectural framework for machine learning in future networks including IMT-2020. The topics are related to Autonomous Networks but differ in focus and emphasis to the TM Forum work. The group has published deliverables on architectural framework, high-level architecture, requirements and discussed topics such as intent, machine learning, orchestrator, ML pipeline, and the need for ML sandboxes. Four important areas are shown in the callouts in Figure 3.
-
-![Figure 3: Overview of ML work in FG ML5G [Y3172] (Callouts added). The diagram illustrates the architectural framework for machine learning in future networks. It shows a Management subsystem (MLFO, ML intent) interacting with an ML sandbox subsystem (Simulated ML underlay networks, ML pipeline subsystem, ML underlay networks). Callouts provide details on MLFO, ML Pipeline, ML Sandbox, and Underlay networks.](af6be343f0c0a8f155f965dcf337b8af_img.jpg)
-
-The diagram illustrates the architectural framework for machine learning in future networks, showing the interaction between various subsystems and components.
-
-- Management subsystem:** Contains "Other management and orchestration functions" and "MLFO" (Machine Learning Functionality Orchestrator). MLFO is connected to "ML intent".
-- ML sandbox subsystem:** Contains "Simulated ML underlay networks" and "ML pipeline subsystem".
-  - ML Pipeline:** Provides an abstraction for handling ML. It is connected to the "ML pipeline subsystem" and "Simulated ML underlay networks".
-  - ML Sandbox:** Provides an environment for test/verify ML. It is connected to the "ML pipeline subsystem" and "Simulated ML underlay networks".
-- ML underlay networks:** Contains "Underlay network 1" and "Underlay network 2". Each network contains "NF 1" through "NF n" (Network Functions).
-  - Underlay networks:** E.g. IMT-2020 networks like 3GPP.
-
-Callouts added to the diagram:
-
-- MLFO:** Manage ML functionality in the network.
-- ML Pipeline:** Provides an abstraction for handling ML.
-- ML Sandbox:** Provides an environment for test/verify ML.
-- Underlay networks:** E.g. IMT-2020 networks like 3GPP.
-
-Y.3172(19)\_F04
-
-Figure 3: Overview of ML work in FG ML5G [Y3172] (Callouts added). The diagram illustrates the architectural framework for machine learning in future networks. It shows a Management subsystem (MLFO, ML intent) interacting with an ML sandbox subsystem (Simulated ML underlay networks, ML pipeline subsystem, ML underlay networks). Callouts provide details on MLFO, ML Pipeline, ML Sandbox, and Underlay networks.
-
-Figure 3. Overview of ML work in FG ML5G [Y3172] (Callouts added)
-
-# 3 Intent in Autonomous Networks
-
-## 3.1 Intent Standardization Efforts
-
-Many standard-developing organizations (SDO) are actively working on the topic of autonomous networks and associated intent-driven management. One of the key building blocks of intent-driven management is the intent meta-model which provides an abstract representation of the schema and rules of the intent model, irrespective of the management domain or specific management layer, and enables the extension of such a model wherever necessary, depending on the context of usage. This is critical because the meta-model of the intent is one of the architectural considerations that can influence the functional blocks required for the autonomous network system to derive the semantic meaning and context of the intent as well as helps to map intent to internal actions without ambiguities or conflicts.
-
-Table 3 lists some of the key standards in the area of intent-driven networking and categorizes the standards by the following dimensions: conception definition, model, architecture, classification (types, taxonomy), domain (scopes), and lastly, the relevant TM Forum AN Intent Category (Business Intent, Service Intent, Resource Intent).
-
-**Table 3. Intent Standards Classification**
-
-|                 | Concept Definition                                                     | Model                                                                                                                                                                               | Architecture                                        | Classification                                               | Domains             | Intent Category            |
-|-----------------|------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------|--------------------------------------------------------------|---------------------|----------------------------|
-| <b>TM Forum</b> | IG 1230                                                                | IG1253                                                                                                                                                                              | IG1251 and IG1253                                   | IG1253A                                                      | FFS in IG1253E      | Business, Service Resource |
-| <b>ZSM/ENI</b>  | ZSM005/<br>ZSM011 (in 2021)                                            | ENI PoC8                                                                                                                                                                            | ENI005, ITANA                                       |                                                              |                     | Service, Resource          |
-| <b>3GPP</b>     | TR 28.812 /TS 28.312                                                   | TR 28.812                                                                                                                                                                           | 28.312                                              | TR 28.812 / TS 28.312                                        | TR 28.812 TS 28.312 | Network / Domain Specific  |
-| <b>IETF</b>     | RFC7575<br><a href="#">draft-irtf-nmrg-ibn-concepts-definitions-03</a> | <a href="#">RFC 8049</a><br><a href="#">RFC 8466</a><br>RFC 8969<br><a href="#">draft-ietf-opsawg-l3sm-l3nm-09</a><br><a href="#">draft-yang-nmrg-network-measurement-intent-01</a> | draft-ietf-opsawg-service-assurance-architecture-00 | <a href="#">draft-irtf-nmrg-ibn-intent-classification-03</a> |                     | Network / Domain Specific  |
-| <b>Other</b>    | MEF071                                                                 | MEF071                                                                                                                                                                              | ITU SG13 Q2 Y.IBN Reqs                              | CCSA                                                         |                     |                            |
-
-TM Forum's AN Project has also published a suite of guides on 'Intent in Autonomous Networks'. See below for the complete list of guides.
-
-1. IG1253 is a set of documents in which each document defines a separate aspect of intent-driven operation:
-2. IG1253 - Intent in Autonomous Networks  
-This is the main overview document. It contains a description of general definitions and operation principles. The documents A-E contain and deeper views into some key topics.
-3. IG1253A - Intent Modeling  
-This document defines the modeling of intent objects as ontology graphs. It introduces the concept of model federation based on a central intent meta-model and separate domain-specific extensions and information models. This document then defines the central and domain-independent intent meta-model.
-4. IG1253B - Intent Information Models (future release)  
-This document adds to the model federation as defined in IG1253A and propose domain-specific extensions and information models.
-5. IG1253C - Intent life cycle management and Interface  
-This document defines the life cycle of intent including the [roles](#) and responsibilities within the life-cycle. It then defines the interface and API used to execute the life-cycle management operations. This includes methods for communicating, modifying and removing intent objects, as well as negotiating intent content.
-6. IG1253D - Intent handler scope and capability management (future release)  
-This document defines a registration and discovery mechanism about the capabilities and scope of operation of distinct intent handler interfaces.
-7. IG1253E - Use cases and examples (future release)  
-This document is a collection of use cases with detailed examples that demonstrate how to apply the principles and use the models and interfaces defined in the IG1253 set of documents.
-
-Separate to the Intent specification work above, TM Forum has also published a study called IG1259 Study of Telecom Industry Intent Meta-Modeling Approaches that examines the various approaches to intent modeling and intent expression languages from across SDOs and open source communities [IG1259].
-
-# 4 Administrative
-
-## 4.1 References
-
-| #       | Title                                                                                                                                                                                                                                                                                | Organization |
-|---------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------|
-| EAI34   | ETSI White Paper No. #34, "Artificial Intelligence and Future Directions for ETSI," 1st Edition, Jun 2020.                                                                                                                                                                           | ETSI         |
-| EAN40   | ETSI White Paper No. #40, "Autonomous Networks, supporting tomorrow's ICT business," 1st edition, Oct 2020.                                                                                                                                                                          | ETSI         |
-| ENI005  | ETSI ENI, "Experiential Networked Intelligence (ENI); System Architecture," GS ENI 005, v2.0.23, Mar 2021.                                                                                                                                                                           | ETSI         |
-| ENI44   | ETSI Whitepaper No. #44, "ENI Vision: Improved Network Experience using Experiential Networked Intelligence," 1st Edition, Mar 2021.                                                                                                                                                 | ETSI         |
-| GANAA4  | ETSI White Paper No. #4, "ETSI GANA as Multi-Layer Artificial Intelligence (AI) Framework for Implementing AI Models for Autonomic Management & Control (AMC) of Networks and Services; and Intent-Based Networking (IBN) via GANA Knowledge Planes (KPs)," Released on 27 Aug 2019. | ETSI         |
-| IG1190  | AI Ops Service Management - a guide of best practices on redesigning complex service management operations processes to handle and govern AI software at scale.                                                                                                                      | TM Forum     |
-| IG1193  | Autonomous Networks Vision                                                                                                                                                                                                                                                           | TM Forum     |
-| IG1218  | Autonomous Networks Business Requirements and Framework v1.1                                                                                                                                                                                                                         | TM Forum     |
-| IG1230  | Autonomous Networks Technical Architecture v1.1                                                                                                                                                                                                                                      | TM Forum     |
-| IG1230A | Autonomous Networks Scenarios Realizations v1.1                                                                                                                                                                                                                                      | TM Forum     |
-| IG1253  | Intent in Autonomous Networks (Suite of guides)                                                                                                                                                                                                                                      | TM Forum     |
-| IG1259  | Study of Telecom Industry Intent Meta-Modeling Approaches v1.0.0                                                                                                                                                                                                                     | TM Forum     |
-| IG1260  | Autonomous Networks Project Deliverable Guide                                                                                                                                                                                                                                        | TM Forum     |
-| Y.3172  | ITU-T, "Architectural framework for machine learning in future networks including IMT-2020," Recommendation ITU-T Y.3172, Jun 2019.                                                                                                                                                  | ITU-T        |
-| Y.3174  | ITU-T, "Framework for data handling to enable machine learning in future networks including IMT-2020," Recommendation ITU-T Y.3174, Feb 2020.                                                                                                                                        | ITU-T        |
-| ZSM002  | ETSI ZSM, "Zero-touch network and Service Management (ZSM); Reference Architecture," GS ZSM 002, v1.1.1, Aug 2019.                                                                                                                                                                   | ETSI         |
-| ZSM005  | ETSI ZSM, "Zero-touch network and Service Management (ZSM); Means of Automation" GR ZSM 005, v1.1.1, May 2020.                                                                                                                                                                       | ETSI         |
-
-## 4.2 Document History
-
-### 4.2.1 Version History
-
-| Version Number | Date Modified             | Modified by:    | Description of changes                                                                                                           |
-|----------------|---------------------------|-----------------|----------------------------------------------------------------------------------------------------------------------------------|
-| 1.1.0          | 25 <sup>th</sup> May 2021 | Kevin McDonnell | Final edits before publication. (No Version 1.0 of Guide exists, V1.1 used to align to companion guides IG1230 and IG1230A v1.1) |
-| 1.1.0          | 28-May-2021               | Alan Pope       | Final edits prior to publication.                                                                                                |
-
-### 4.2.2 Release History
-
-| Release Status | Date Modified                  | Created by:      | Description of changes                       |
-|----------------|--------------------------------|------------------|----------------------------------------------|
-| Production     | 23 <sup>rd</sup> November 2020 | Kevin McDonnell  | Originally published as Part 3 of IG1230 1.0 |
-| Pre-production | 28-May-2021                    | Alan Pope        | Initial release of v1.1.0                    |
-| Production     | 26-Jul-2021                    | Adrienne Walcott | Updated to reflect TM Forum Approved Status  |
-
-## 4.3 Acknowledgements
-
-This document was prepared by members of the TM Forum Autonomous Networks project.
-
-### 4.3.1 Guide Lead & Author
-
-| Member          | Title                                   | Company |
-|-----------------|-----------------------------------------|---------|
-| Kevin McDonnell | Senior Director, Intelligent Automation | Huawei  |
-
-### 4.3.2 Main Contributors
-
-| Member          | Title          | Company |
-|-----------------|----------------|---------|
-| Wang Lei        | Systems Expert | Huawei  |
-| Wang Xu         | Systems Expert | Huawei  |
-| Xie Yuan        | Systems Expert | Huawei  |
-| Zheng Guangying | Systems Expert | Huawei  |
-
-### 4.3.3 Additional Inputs
-
-| Member              | Title                   | Company      |
-|---------------------|-------------------------|--------------|
-| Abdul Majid Hussain | Solutions Architect     | Telstra      |
-| Abinash Vishwakarma | Lead Business Analyst   | Netcracker   |
-| Andy Corston-Petrie | Senior Research Manager | BT Group plc |
-| Brad Peters         | Architect               | NBNCo Ltd    |
-| Christian Maître    | VP Smart City           | Orange       |
-
-| Member              | Title                                                          | Company                |
-|---------------------|----------------------------------------------------------------|------------------------|
-| Dong Sun            | Chief Business Strategist, Digital Transformation              | Futurewei Technologies |
-| Emmanuel A. Otchere | Chief Technical Expert<br>VP, Standards & Industry Development | Huawei                 |
-| Joe Isaac           | Principal Architect                                            | Wipro Technologies     |
-| Johanne Mayer       | Consultant                                                     | Ciena                  |
-| Liu Hongbo          | Deputy General Manager, Intelligent Network Center             | China Unicom           |
-| Luigi Licciardi     | Consultant, Executive Advisor                                  | Huawei                 |
-| Manoj Nair          | Senior Solutions Architect, CTO Office                         | Netcracker             |
-| Min He              | Chief Architect                                                | Futurewei Technologies |
-| Qiao Zizhi          | Senior Engineer, Intelligent Network Center                    | China Unicom           |
-| Steve Iatropoulos   | Client & Industry CTO                                          | Microsoft              |
-| Tayeb Ben Meriem    | Senior Standardization Manager                                 | Orange                 |
-| Thierry Reynard     | OSS Consulting Manager                                         | ETIYA                  |
-| Vance Shipley       | CEO                                                            | Sigscale               |
-
-### 4.3.4 TM Forum Staff
-
-| TM Forum            | Title                                          | Company  |
-|---------------------|------------------------------------------------|----------|
-| Aaron Boasman-Patel | Vice President, AI, Customer Experience & Data | TM Forum |
-| Alan Pope           | Collaboration Manager                          | TM Forum |
-| David Milham        | Chief Architect                                | TM Forum |
-| Ian Turkington      | VP, Architecture & APIs                        | TM Forum |
-| W. George Glass     | CTO                                            | TM Forum |