Cache Selection in Dynamic D2D Multicast Networks Using Inhomogeneous Markov Model

This article presents a user spatio-temporal behavior aware cache selection framework to facilitate device-to-device multicast (D2MD) communication that minimizes the number of caches required while achieving a desired user load on the cellular network. Consequently, it alleviates the caching load on the cellular network. The optimization problem formulated to minimize the number of caches is combinatorial in nature with an exponential search space. Hence, a greedy algorithm for cache selection is proposed to reduce the search space. It has been shown that the greedy algorithm has a complexity O(K
²
) where K is the number of users. A real-world location-based inhomogeneous Markov chain is presented to model the joint spatio-temporal behavior of the users. The diurnal variation of observable user load on the core network as well as sum-rate of non-caching users has been demonstrated for real-world location data traces. It has been shown that the proposed framework not only achieves the desired user load but also helps in improving the sum-rate of noncaching users as compared to the mobility-unaware selection of caches.