An efficient task scheduling in a cloud computing environment using hybrid Genetic Algorithm - Particle Swarm Optimization (GA-PSO) algorithm

Abstract

Cloud computing provides the computational machines as a support of the clients utilizing cloud organize. In cloud computing, the user inputs are executed with required machines to convey the administrations. Numerous task scheduling methods are utilized to plan the client tasks to the machines. In this paper, another successful hybrid task scheduling is proposed to minimize the total execution time using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithms. In hybrid Genetic Algorithm - Particle Swarm Optimization (GA-PSO) algorithm, PSO helped GA to obtain better results compare to a standard genetic algorithm, Min-Min, and Max-Min algorithms results.