Network slicing, a cornerstone technology for future networks, enables the creation of customized virtual networks on a shared physical infrastructure. This fosters innovation and agility by providing dedicated resources tailored to specific applications. However, current orchestration and management approaches face limitations in handling the complexity of new service demands within multi-administrative domain environments. This paper proposes a future vision for network slicing powered by Large Language Models (LLMs) and multi-agent systems, offering a framework that can be integrated with existing Management and Orchestration (MANO) frameworks. This framework leverages LLMs to translate user intent into technical requirements, map network functions to infrastructure, and manage the entire slice lifecycle, while multi-agent systems facilitate collaboration across different administrative domains. We also discuss the challenges associated with implementing this framework and potential solutions to mitigate them.

翻译：网络切片作为未来网络的基石技术，能够在共享物理基础设施上创建定制化虚拟网络。通过为特定应用提供专用资源，该技术促进了创新和敏捷性。然而，当前编排与管理方法在多管理域环境下应对新型服务需求的复杂性时面临诸多限制。本文提出了一种由大语言模型（LLMs）与多智能体系统驱动的网络切片未来愿景，构建了可与现有管理编排（MANO）框架集成的解决方案。该框架利用大语言模型将用户意图转化为技术需求、将网络功能映射至基础设施、并管理整个切片生命周期，同时通过多智能体系统实现跨管理域的协同合作。我们进一步探讨了该框架实施过程中面临的挑战及潜在缓解方案。