Towards Autonomous Network Management: AI-Driven Framework for Intelligent Log Analysis, Troubleshooting and Documentation
Description
Modern network management is increasingly complex, requiring administrators to handle vast amounts of log data from diverse sources, leading to inefficiencies, errors, and operational challenges. In this work, we propose a novel AI-driven framework that integrates Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) and human- in-the-loop process to automate network management tasks such as log analysis, troubleshooting recommendations, and documentation generation. This study aims to enhance network reliability, reduce operational complexity, and move forward to autonomous network management.
This paper has been withdrawn.