Efficiently allocating distributed caching resources in future smart networks

During the last decade, Internet Service Providers (ISPs) infrastructure has undergone a major metamorphosis driven by new networking paradigms, namely: Software Defined Networks (SDN) and Network Function Virtualization (NFV). The upcoming advent of 5G will certainly represent an important achievement of this evolution. In this context, static (planning) or dynamic (on-demand) caching resources placement remains an open issue. In this paper, we propose a new technique to achieve the best trade-off between the centralization of resources and their distribution, through an efficient placement of caching resources. To do so, we model the cache resources allocation problem as a multi-objective optimization problem, which is solved using Greedy Randomized Adaptive Search Procedures (GRASP). The obtained results confirm the quality of the out-comes compared to an exhaustive search method and show how a cache allocation solution depends on the network's parameters and on the performance metrics that we want to optimize.