An Intent-based Networks Framework based on Large Language Models

Motivated by the increasing complexity of today's communication networks, autonomous networks (AN) have recently attracted much attention from industry and academia. Automated network configurations through intent-based networking (IBN) is the first and crucial step towards AN. In this paper, we focus on realizing automated network configurations leveraging the rapid evolution of large language models (LLMs). We proposed a framework based on modular design integrated with LLMs. Our preliminary results confirm that LLMs have great potential in IBN and can serve as an important point on the way to realizing AN while keeping data privacy and integrity of configuration results. However, several challenges and open questions remain to be addressed.