Joint Optimization of Edge Caching and Collective Recommendation for Offloading Maximization

This paper studies the optimization of the recommendation-enhanced wireless edge caching. Different from existing works that mainly considered the personalized recommendation, we study the combination of collective recommendation and edge caching, and jointly optimize the probabilistic recommendation and probabilistic caching policies, aimed at maximizing the average offloading probability. We propose two algorithms to solve the joint optimization problem, and conduct a data-based analysis for the impact of collective recommendation on request probability of users. Simulation results show the increased traffic offloading brought by the proposed method.