Data-Driven Online Resource Allocation for User Experience Improvement in Mobile Edge Clouds

no code implementations • 6 Apr 2024 • Liqun Fu, Jingwen Tong, Tongtong Lin, Jun Zhang

Due to the learned objective model is typically non-convex and challenging to solve in real-time, we leverage the Lyapunov optimization to decouple the long-term average constraint and apply the prime-dual method to solve this decoupled resource allocation problem.

From Learning to Analytics: Improving Model Efficacy with Goal-Directed Client Selection

no code implementations • 30 Mar 2024 • Jingwen Tong, Zhenzhen Chen, Liqun Fu, Jun Zhang, Zhu Han

To address the challenges posed by system and data heterogeneities in the FL process, we study a goal-directed client selection problem based on the model analytics framework by selecting a subset of clients for the model training.

Federated Learning