Adaptive Peer Selection Strategy in P2P-VoD Systems Based on Dynamic Metaheuristic

During the past decade, Peer-to-Peer Video-on Demand (VoD) systems have proved their efficiency for large deployments. They raise new challenges such as peers resource allocation. Most literature on resource allocation tackle the problem with optimal static rules found at offline study of the system. In this paper, we use a dynamic metaheuristic, called Multiple Local-Search Algorithm for Dynamic Optimization (MLSDO) to optimize the problem at hand. The obtained results show that using a dynamic resource allocation reduces the rejection rate while enhancing the entropy of the system, in the face of a dynamically changing title demand.