An Efficient Task Scheduling Using GWO-PSO Algorithm in a Cloud Computing Environment

Abstract

Nowadays, cloud computing becomes a major technology that provides services to users by integrating Internet technology. Scheduling of user tasks plays a vital role in a cloud environment. An efficient task scheduling method is required to manage the resources for executing user tasks in order to attain better result in QoS parameters. Task scheduling is a kind of non-deterministic polynomial (NP) hard problem, which can be solved using optimization algorithms. This paper presents a novel hybrid method by combining grey wolf optimization (GWO) and particle swarm optimization algorithm (PSO). The proposed method optimizes the result in order to maintain the makespan as a minimum. PSO improves the optimization performance of grey wolf optimization in the proposed method. The proposed algorithm performance is evaluated and analysed with GA and GWO algorithms. The proposed GWO-PSO algorithm results are better than the GWO and GA algorithms in terms of response time and makespan.