Intent-Based Networking (IBN) management has emerged as an alternative approach to simplify network configuration and management by abstracting the complexities of low-level configurations. Existing IBN solutions typically rely on human-readable structures like JSON or YAML to define Intents, which still require expertise in understanding these structures. A natural evolution of IBN is to use natural language instead of defined structures. However, this approach introduces complexities related to natural language understanding. Fortunately, Large Language Models (LLMs) offer a promising solution. In this paper: (i) We propose a novel LLM-centric Intent Life-Cycle (LC) management architecture designed to configure and manage network services using natural language. The architecture spans the complete Intent LC, encompassing decomposition, translation, negotiation, activation, and assurance; (ii) We identify key open issues and challenges related to IBN within our proposed architecture; (iii) We demonstrate the effectiveness of the architecture by developing a component within the EURECOM 5G facility [1] , leveraging LLMs to implement the essential Intent LC procedures; (iv) We validate the proposed system through realworld deployment, showcasing its capability to define, decompose, translate, and activate Intents using natural language.

中文翻译：

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下一代网络基于意图的管理： LLM为中心的方法


基于意图的网络 (IBN) 管理已成为一种替代方法，通过抽象低级配置的复杂性来简化网络配置和管理。现有的 IBN 解决方案通常依赖于人类可读的结构（例如 JSON 或 YAML）来定义 Intent，这仍然需要专业知识来理解这些结构。 IBN 的自然演变是使用自然语言而不是定义的结构。然而，这种方法引入了与自然语言理解相关的复杂性。幸运的是，大型语言模型（ LLMs ）提供了一个有前途的解决方案。在本文中：（i）我们提出了一种新颖的以LLM为中心的意图生命周期（LC）管理架构，旨在使用自然语言配置和管理网络服务。该架构涵盖了完整的意图LC，包括分解、翻译、协商、激活和保证； (ii) 我们在提议的架构中确定与 IBN 相关的关键未决问题和挑战； (iii) 我们通过在 EURECOM 5G 设施 [1] 内开发一个组件，利用LLMs实施必要的意向 LC 程序，证明了该架构的有效性； (iv) 我们通过现实世界的部署来验证所提出的系统，展示其使用自然语言定义、分解、翻译和激活意图的能力。