STUDY OF MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR TASK SCHEDULING IN CLOUD COMPUTING

Abstract

Even though there is much advancement in the era of computers and Internet of Things (IoT) with respect to
responsiveness, reliability and flexibility, still there is a room for improvement in scheduling, optimal resource allocation and
management algorithms since these algorithms come under NP-hard and NP-complete complexity classes. Hence, there is a
need to address these set of challenging problems using different techniques. In this paper, we mainly focus on scheduling the
tasks using Modified Particle Swarm optimization algorithm. This algorithm reduced execution time and average response
time with efficient utilization of cloud resource.