M-GRASP: A GRASP With Memory for Latency-Aware Partitioning Methods in DVE Systems

A necessary condition for providing quality of service to distributed virtual environments (DVEs) is to provide a system response below a maximum threshold to the client computers. In this sense, latency-aware partitioning methods try to provide response times below the threshold to the maximum number of client computers as possible. These partitioning methods should find an assignment of clients to servers that optimizes system throughput, system latency, and partitioning efficiency. In this paper, we present a new algorithm based on greedy randomized adaptive search procedure with memory for finding the best solutions as possible to this problem. We take into account several different alternatives in order to design both the constructive phase and the local search phase of this multistart metaheuristic for combinatorial problems. Additionally, we enhance this basic approach with some intensification strategies that improve the efficiency of the basic search method. Performance evaluation results show that the new algorithm increases the performance provided by other metaheuristics when applied to solve the latency-aware partitioning problem in DVE systems.