IEEE Networking Letters, 20 November 2024
This work presents Maestro, a collaborative framework leveraging Large Language Models (LLMs) for automation of shared networks. Maestro enables conflict resolution and collaboration among stakeholders in a shared intent-based 6G network by abstracting diverse network infrastructures into declarative intents across business, service, and network planes. LLM-based agents negotiate resources, mediated by Maestro to achieve consensus that aligns multi-party business and network goals. Evaluation on a 5G Open RAN testbed reveals that integrating LLMs with optimization tools and contextual units builds autonomous agents with comparable accuracy to the state-of-the-art algorithms while being flexible to spatio-temporal business and network variability.
Type:
Journal
Date:
2024-11-20
Department:
Communication systems
Eurecom Ref:
7973
Copyright:
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