Content Delivery in Mobility-Aware D2D Caching Networks

The massive data exchange between base stations and network backhaul creates a strong overhead on mobile networks, especially at peak times. This motivates researchers to think about the proactive caching concept which depends mainly on caching some of the expected data items during off-peak times. The caching problem consists of two distinct phases, placement phase and delivery phase. In this work, we consider a mobility aware device-to-device (D2D) caching network. We assume that data contents were already cached in users devices during the content placement phase and we focus on the content delivery phase. The social relationships between users allows us to predict their meeting probabilities at some places. Moreover, the similarity in users interest increases the probability of finding requested data items at nearby users and hence increases the hit probability. This motivates us to study the effect of sociality and interest similarity on the content delivery. We study how to minimize users average cost by obtaining the requested data items from nearby users, via D2D communication, instead of going back to the base station. Dynamic programming is used to find an optimal content delivery policy. Due to the complexity of the optimal policy, we introduce a suboptimal algorithm and compare between them. We show, through numerical results, that the proposed algorithm has a significant performance, compared to the optimal content delivery policy, for a large enough number of time slots.