Edge Association

Edge association research focuses on optimizing the connection between devices and edge servers for efficient and privacy-preserving machine learning. Current efforts concentrate on developing lightweight federated learning frameworks, improving resource allocation through algorithms like reinforcement learning, and minimizing latency and energy consumption via hierarchical structures and adaptive model compression techniques. This work is significant for enabling the deployment of large language models and other computationally intensive applications on resource-constrained edge devices, improving both performance and data privacy.