Aiming to outline the vision of realizing automated and intelligent communication networks in the era of intelligence, this book describes the development history, application scenarios, theories, architectures, and key technologies of Huawei's Autonomous Driving Network (ADN) solution.
In the book, the authors explain the design of the top-level architecture, hierarchical architecture (ANE, NetGraph, and AI Native NE), and key feature architecture (distributed AI and endogenous security) that underpin Huawei's ADN solution. The book delves into various key technologies, including trustworthy AI, distributed AI, digital twin, network simulation, digitization of knowledge and expertise, human-machine symbiosis, NE endogenous intelligence, and endogenous security. It also provides an overview of the standards and level evaluation methods defined by industry and standards organizations, and uses Huawei's ADN solution as an example to illustrate how to implement AN.
Autonomous Networks (AN), a product of the mutual development between network and digital technologies, has become an indispensable capability for future networks. It will help coordinate network devices and management systems, improve network intelligence, enable intelligent services, and promote transformation toward digital, automated, and intelligent infrastructure.
The emergence of 5G and other next-generation information technologies is expediting today’s innovations and breakthroughs. As computing power and networks become more deeply integrated, new information infrastructures are enabling digital upgrade and reconstruction of production organizations, objects, tools, and modes in various industries – this in turn is facilitating digital transformation across society as a whole. One of the major driving forces powering the industrialization of digital technologies and the digitalization of various industries is AN, which offers a Zero-X (zero-wait, zero-trouble, and zero-touch) and Self-X (self-configuration, self-healing, and self-optimizing) experience.
This book is an essential reference for professionals and researchers who want to gain a deeper understanding of automated and intelligent communication networks and their applications.
Author(s): Wenshuan Dang, River Huang, Yijun Yu
Publisher: CRC Press
Year: 2023
Language: English
Pages: 400
Cover
Half Title
Title Page
Copyright Page
Table of Contents
Foreword I
Foreword II
Foreword III
Foreword IV
Preface
Introduction
Chapter 1 Birth of ADN
1.1 Architecture Evolution of Modern Communications Networks
1.2 Driving Forces of Network Automation and Intelligence
1.2.1 Network O&M Efficiency
1.2.2 New Scenarios and Services
1.2.3 Social Responsibility and Sustainable Development
1.3 Two Approaches to Network Automation and Intelligence
1.4 Vision of ADN
1.5 Levels of ADN
1.6 Development of the an Industry
Notes
References
Chapter 2 Application Scenarios of ADN
2.1 Mobile ADN
2.1.1 Emergency Assurance of Integrated Terrestrial and Non-Terrestrial Communications
2.1.2 All-Wireless Enterprise LAN
2.2 Fixed ADN
2.2.1 Secure, Reliable, and Immersive Remote Office
2.2.2 Remote Control of Deterministic WAN
2.3 Network Technology Innovation
Reference
Chapter 3 Fundamental Theories of ADN
3.1 Network Adaptive Control Theory
3.1.1 Driving Forces Behind Network Adaptive Control
3.1.2 Fundamental Theories of Network Adaptive Control
3.2 Network Cognition Theory
3.2.1 Network Cognition is the Basis of ADN
3.2.2 ADN Cognition System and Its Features
3.2.3 Key Elements in ADN Cognition
3.3 User and Environment Agent Model Theory
3.3.1 Driving Forces Behind User and Environment Agents
3.3.2 Fundamental Theories of User and Environment Agents
3.4 Practical Application of Theories
3.4.1 Practices of Adaptive Control in Aerospace
3.4.2 IBM’s Practices from Autonomic Computing to Cognitive Computing
3.4.3 Practices of User and Environment Agents
References
Chapter 4 Reference Architecture of ADN
4.1 Top-Level Architecture
4.1.1 General Design Principles
4.1.2 Special Design Principles
4.1.3 Logical View of the Top-Level Architecture
4.1.4 Architecture Characteristics
4.2 ANE
4.2.1 Concepts
4.2.2 Core Architecture Design Principles
4.2.3 Target Reference Architecture
4.2.4 Modules and Components
4.2.5 Key Characteristics of the Architecture
4.3 Netgraph
4.3.1 Concepts
4.3.2 Core Architecture Design Principles
4.3.3 Target Reference Architecture
4.3.4 Modules and Components
4.3.5 Key Characteristics of the Architecture
4.4 AI Native NES
4.4.1 Concepts
4.4.2 Core Architecture Design Principles
4.4.3 Target Reference Architecture
4.4.4 Modules and Components
4.4.5 Key Characteristics of the Architecture
4.5 Distributed AI Architecture
4.5.1 Concepts
4.5.2 Core Architecture Design Principles
4.5.3 Target Reference Architecture
4.5.4 Modules and Components
4.5.5 Key Characteristics of the Architecture
4.6 Intrinsic Security
4.6.1 Concepts
4.6.2 Challenges
4.6.3 Core Architecture Design Principles
4.6.4 Target Reference Architecture
4.6.5 Modules and Components
4.6.6 Key Characteristics of the Architecture
References
Chapter 5 Key Technologies of ADN
5.1 Trustworthy Network AI
5.1.1 Background and Motivation
5.1.2 Technology Insights
5.1.3 Key Technical Solutions
5.1.4 Technology Prospects
5.2 Distributed Network AI
5.2.1 Background and Motivation
5.2.2 Technology Insights
5.2.3 Key Technical Solutions
5.2.4 Technology Prospects
5.3 Network Digital Twin
5.3.1 Background and Motivation
5.3.2 Technology Insights
5.3.3 Key Technical Solutions
5.3.4 Technology Prospects
5.4 Network Simulation Technology
5.4.1 Background and Motivation
5.4.2 Technology Insights
5.4.3 Key Technical Solutions
5.4.4 Technology Prospects
5.5 Digitalization of Network Knowledge and Expertise
5.5.1 Background and Motivation
5.5.2 Technology Insights
5.5.3 Key Technical Solutions
5.5.4 Technology Prospects
5.6 Network Human-Machine Symbiosis Technology
5.6.1 Background and Motivation
5.6.2 Technology Insights
5.6.3 Key Technical Solutions
5.6.4 Technology Prospects
5.7 Ne Endogenous Intelligence Technology
5.7.1 Background and Motivation
5.7.2 Technology Insights
5.7.3 Key Technical Solutions
5.7.4 Technology Prospects
5.8 Network Endogenous Security Technology
5.8.1 Background and Motivation
5.8.2 Technology Insights
5.8.3 Key Technical Solutions
5.8.4 Technology Prospects
5.9 Summary
References
Chapter 6 Industry Standards
6.1 International Standards
6.1.1 General Standards
6.1.2 Mobile Communications Standards
6.1.3 Transport, Access, and Bearer Network Standards
6.2 Chinese Standards
6.2.1 General Standards
6.2.2 Mobile Communications Standards
6.2.3 Transport, Access, and Bearer Network Standards
6.3 Cross-Organization Standards Collaboration
References
Chapter 7 Level Evaluation of ADN
7.1 Decomposing Operation Flows and Tasks
7.2 Refining the Requirements on Human-Machine Division of Labor for Operation Tasks
7.3 Specifying the Scenarios of Evaluation Objects
7.4 Level Evaluation Method and Example
References
Chapter 8 ADN Solution
8.1 Intelligentran – Wireless ADN
8.1.1 Highlights
8.1.2 Key Use Cases
8.2 Intelligentcore – Core Network ADN
8.2.1 Highlights
8.2.2 Key Use Cases
8.3 Intelligentwan – IP ADN
8.3.1 Highlights
8.3.2 Key Use Cases
8.4 Intelligentcampusnetwork – Enterprise Campus ADN
8.4.1 Highlights
8.4.2 Key Use Cases
8.5 Intelligentfabric – DC ADN
8.5.1 Highlights
8.5.2 Key Use Cases
8.6 Intelligentfan – All-Optical Access ADN
8.6.1 Highlights
8.6.2 Key Use Cases
8.7 Intelligentotn – All-Optical Transport ADN
8.7.1 Highlights
8.7.2 Key Use Cases
8.8 Intelligentserviceengine – Intelligent O&M
8.8.1 AUTIN: Intelligent O&M
8.8.2 SmartCare: Superior Experience
8.8.3 ADO: Business Enablement
Chapter 9 Summary and Outlook
Note
Glossary
