Hermes：一种面向自主网络的大型语言模型框架

Hermes: A Large Language Model Framework on the Journey to Autonomous Networks

November 10, 2024

作者: Fadhel Ayed, Ali Maatouk, Nicola Piovesan, Antonio De Domenico, Merouane Debbah, Zhi-Quan Luo

cs.AI

摘要

随着移动网络系统日益复杂，推动自动化细胞网络运营的努力也在增加。尽管取得了进展，由于依赖人为干预来对网络行为建模并定义满足目标要求的策略，完全自主目前仍然难以实现。网络数字孪生（NDTs）显示出增强网络智能的潜力，但这项技术的成功实施受到特定用例架构的限制，限制了其在推进网络自主性方面的作用。需要更具能力的网络智能，或者称之为“电信大脑”，以实现对细胞网络的无缝自主管理。大型语言模型（LLMs）已被视为实现这一愿景的潜在推动者，但在网络建模方面面临挑战，尤其是在推理和处理多样数据类型方面。为了解决这些差距，我们引入了Hermes，这是一系列LLM代理的链，通过结构化和可解释的逻辑步骤使用“蓝图”来构建NDT实例。Hermes实现了对多样化用例和配置进行自动、可靠和准确的网络建模，从而标志着朝着完全自主网络运营迈出了一步。

English

The drive toward automating cellular network operations has grown with the increasing complexity of these systems. Despite advancements, full autonomy currently remains out of reach due to reliance on human intervention for modeling network behaviors and defining policies to meet target requirements. Network Digital Twins (NDTs) have shown promise in enhancing network intelligence, but the successful implementation of this technology is constrained by use case-specific architectures, limiting its role in advancing network autonomy. A more capable network intelligence, or "telecommunications brain", is needed to enable seamless, autonomous management of cellular network. Large Language Models (LLMs) have emerged as potential enablers for this vision but face challenges in network modeling, especially in reasoning and handling diverse data types. To address these gaps, we introduce Hermes, a chain of LLM agents that uses "blueprints" for constructing NDT instances through structured and explainable logical steps. Hermes allows automatic, reliable, and accurate network modeling of diverse use cases and configurations, thus marking progress toward fully autonomous network operations.