To reap its full benefits, 5G must evolve into a scalable decentralized architecture by exploiting intelligence ubiquitously and securely across different technologies, network layers, and segments. In this article, we propose end-to-end and ubiquitous secure machine learning (ML)-powered intent-based networking (IBN). The IBN framework is aware of its state and context to autonomously take proactive actions for service assurance. It is integrated in a zero-touch control and orchestration framework featuring an ML function orchestrator to manage ML pipelines. The objective is to create an elastic and dynamic infrastructure supporting per-domain and end-to-end network and services operation. The solution is supported by a radio access network and forwarding plane, and a cloud/edge virtualization infrastructure with ML acceleration. The resulting framework supports application-level resilience and intelligence through replication and elasticity. An illustrative intelligent application use case is presented.

中文翻译：

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端到端基于意图的网络


为了充分发挥其优势，5G 必须通过跨不同技术、网络层和细分市场安全地利用无处不在的智能，发展成为可扩展的去中心化架构。在本文中，我们提出了端到端且无处不在的安全机器学习 (ML) 支持的基于意图的网络 (IBN)。 IBN 框架了解其状态和上下文，可以自主采取主动行动来保证服务。它集成在零接触控制和编排框架中，该框架具有 ML 功能编排器来管理 ML 管道。目标是创建一个弹性和动态的基础设施，支持每个域和端到端的网络和服务运营。该解决方案由无线接入网络和转发平面以及具有机器学习加速功能的云/边缘虚拟化基础设施提供支持。由此产生的框架通过复制和弹性支持应用程序级的弹性和智能。提出了一个说明性的智能应用程序用例。