LLM-ASF6G: LLM-Based Algorithm Selection Framework for 6G Network Service Optimization

The integration of cloud computing into mobile networks has unlocked new possibilities through a unified and abstract infrastructure. However, this convergence introduced significant complexity, emphasizing the critical need for innovative service management and orchestration techniques. Despite considerable efforts to incorporate automation for optimizing network services, no single algorithm can achieve optimal performance across all spatial and temporal conditions. To address this challenge, we propose LLM-ASF6G, a novel algorithm selection framework for 6 G network service orchestration, designed for algorithmic optimization across both pre-deployment planning and post-deployment operational phases. The proposed framework dynamically selects the most suitable optimization algorithm based on real-time performance metrics and user-defined preferences from a diverse pool of algorithms, techniques and strategies. We evaluate the performance of LLM-ASF6G using different LLM to assess its feasibility for real-world deployment and implementation.