Joint Optimization for Social Content Delivery in Heterogeneous Wireless Networks

Over the past decade, success of social networks has significantly reshaped how people consume information. Recommendation of contents based on user profiles is well-received. However, as users become dominantly mobile in content consumption, little is done to consider the optimization regarding the wireless environment. In this paper, we investigate a centralized wireless content delivery system with heterogeneous base stations, aiming to optimize overall user rewards given the capacity constraints of the wireless networks. We propose a scalable two-phase scheduling framework, consisting of: 1) distributed delivery decisions by each base station, and 2) resource consolidation by the system. Results indicate this novel joint optimization approach is both efficient and scalable.