Efficient task allocation approach using genetic algorithm for cloud environment

As the number of cloud applications is rising exponentially, efficient allocation of these tasks among multiple computing machines ensuring the quality of service and better profit to the cloud service providers is a challenge. Effective task allocation approach needs to be developed considering a number of objectives while making allocation decisions, such as less energy consumption and quick response, in order to make the best resource allocation satisfying the cloud user requirements and improving the overall performance of the cloud computing environment. Hence, in this paper, Genetic Algorithm based efficient task allocation approach has been proposed for achieving the reduced task completion time by making wise allocation decisions. This proposed algorithm has been simulated using cloudsim toolkit and the performance is evaluated by comparing with greedy and simple allocation methods on a set of parameters like makespan and throughput for task scheduling. The evaluation results have shown the better throughput with the proposed approach.