意图驱动端到端网络切片编排与控制

doi:10.11959/j.issn.1000-0801.2023176

Abstract

Abstract:

The 6G system will realize diversified and customized on-demand network services for thousands of industries.End-to-end network slicing can provide users with on-demand and flexible service guarantees.However, the existing network service orchestration and control based on network slicing has problems such as high manual participation, high configuration complexity, and high operation and maintenance cost.Therefore, a solution is urgently needed to meet these challenges.Intent-driven network has the characteristics of flexible reconfiguration and adaptive policy optimization, which can improve the user’s end-to-end service experience.An intent-driven end-to-end network slicing orchestration and control system architecture was proposed, which consisted of business application layer, intent-enabled layer and infrastructure layer.On this basis, the intent parsing module, orchestration and control module were designed.Furthermore, a utility evaluation model was constructed from the perspectives of user satisfaction and system intelligence, and system utility was evaluated through simulation.

Key words: intent-driven network, end-to-end network slicing, orchestration and control, utility evaluation, The National Key Research and Development Program of China

CLC Number:

TP393

Xiaoxue ZHAO, Fuguo XUE, Lulu ZHANG, Ying OUYANG, Chungang YANG. Intent-driven end-to-end network slicing orchestration and control[J]. Telecommunications Science, 2023, 39(9): 1-11.

Figures/Tables 11

References 24

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文献	应用场景	研究内容
[10]	网络切片编排	提出了一种基于意图的端到端网络切片架构，结合深度学习能够有效地预测网络资源状态，实现网络配置和网络管控自动执行
[11]	网络服务编排	提出了一个网络服务编排意图管理系统，用户服务意图可以被转换为编排器可识别的配置文件，之后下发到底层中，实现了网络服务编排
[12]	多域SDN/NFV管理和编排	提出了一个跨多个技术领域的端到端网络管理和编排架构以及基于意图的 NBI，该架构受到ETSI提出的MANO框架的启发
[13]	端到端IDN编排	提出了一个灵活通用的意图定义和端到端意图驱动网络系统体系结构，并对意图驱动网络管控系统的核心方面以及相关的意图建模进行了全面的讨论，以支持它们的标准化

等级	需求映射	数据采集	分析	决策	执行
L0	人工操作	人工操作	人工操作	人工操作	人工操作
L1	人工操作	在预设的场景下可由工具辅助自动完成数据采集	人工操作	人工操作	基本由系统自动完成，少数需要人工参与
L2	人工操作	在多数场景下依据预设规则自动采集数据	在部分预设场景下可依据静态策略自动分析	人工操作	系统自动完成
L3	人工操作	系统自动完成	在多数场景下可自动完成分析	在预设场景下系统可辅助人工自动完成决策	系统自动完成
L4	部分预设场景系统自动完成	系统自动完成（系统自定义采集规则）	系统自动完成（系统自动更新分析策略）	在多数场景下可自动完成决策	系统自动完成

Intent-driven end-to-end network slicing orchestration and control

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Figures/Tables 11

References 24

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