Large Language Model-Driven Cross-Domain Orchestration Using Multi-Agent Workflow

TL;DR

This paper presents a multi-agent system driven by large language models to perform complex, cross-domain network operations involving topology retrieval, optimization, and physical switching, demonstrating collaborative AI capabilities.

Contribution

It introduces a novel multi-agent framework utilizing large language models for orchestrating diverse network tasks across multiple domains.

Findings

Successful real-time topology retrieval

Effective network optimization with physical models

Robotic fiber switching demonstration

Abstract

We showcase an application that leverages multiple agents, powered by large language models and integrated tools, to collaboratively solve complex network operation tasks across various domains. The tasks include real-time topology retrieval, network optimization using physical models, and fiber switching facilitated by a robotic arm.