Effect of Acceleration Coefficient on Particle Swarm optimization for Task Scheduling in Cloud Computing

Abstract

Cloud computing emerges as a powerful platform to deliver IT services online. Due to the rapid development of cloud computing the user's dependence on the cloud has increased and hence user request per unit time is increases. Now scheduling and serving the user requests is a major challenge. Particle swarm optimization as a heuristic algorithm is the most suitable algorithm in such scenario to serve user requests for the most appropriate resources. Author written this research paper in continuation with previous research paper called Modified particle swarm optimization (MPSO) in which author controlled the inertia weight in PSO to find the best cost. This research paper investigates the effect of acceleration coefficient to achieve the best cost. The implementation results of PSO with different acceleration coefficient are produced and compared. Author has use MATLab to test the effect of acceleration coefficient on fitness value and also implemented in CloudSim simulator to test variation in execution time in various scenario. The purpose of author is also to test correctness of Reyes-Sierra and Coello [19] suggested acceleration coefficient.