An energy-aware method for data replication in the cloud environments using a Tabu search and particle swarm optimization algorithm

摘要

Cloud computing is a type of parallel, configurable, and flexible system, which refers to the provisionof applications on virtual data centers. However, reducing the energy consumption andalso maintaining high computation capacity have become timely and important challenges. Theconcept of replication is used to face these challenges. By increasing the number of data replicas,the energy consumption, the performance, and also the cost of creating and maintaining newreplicas also are increased.Deciding on the number of required replicas and their location on thecloud system is an NP-hard problem. In this paper, the problem is formulated as an optimizationproblem and a hybrid metaheuristic algorithm is offered to solve it. The algorithm uses the globalsearch capability of the Particle Swarm Optimization (PSO) algorithm and the local search capabilityof the Tabu Search (TS) to get high-quality solutions. The efficiency of the method is shownby comparing it with simple PSO, TS, and Ant Colony Optimization (ACO) algorithm on differenttest cases. The obtained results indicate that the method outperforms all of them in terms ofconsumed energy and cost.