Federated Learning Assisted Edge Caching Scheme Based on Lightweight Architecture DDPM

Abstract

Edge caching is an emerging technology that empowers caching units at edge nodes, allowing users to fetch contents of interest that have been pre-cached at the edge nodes. The key to pre-caching is to maximize the cache hit percentage for cached content without compromising users' privacy. In this letter, we propose a federated learning (FL) assisted edge caching scheme based on lightweight architecture denoising diffusion probabilistic model (LDPM). Our simulation results verify that our proposed scheme achieves a higher cache hit percentage compared to existing FL-based methods and baseline methods.

This paper has been submitted to IEEE letters. The source code has been released at: https://github.com/qiongwu86/Federated-Learning-Assisted-Edge-Caching-Scheme-Based-on-Lightweight-Architecture-DDPM