Cloud Computing Task Scheduling Policy Based on Improved Particle Swarm Optimization

Abstract

The task scheduling policy is the important factors for achieving efficient calculation in a cloud computing environment. This article put forwards a task scheduling method based on improved particle swarm algorithm against the present inefficiency. Particle Swarm Optimization (PSO) algorithm is used to solve task scheduling optimization by introducing the iterative selection operator. Improved particle swarm optimization algorithm (IPSO) can improve the ability of the optimization, as much as possible avoiding falling into a local optimum. The convergence effect is so better that the task scheduling time costs can be reduced. By simulation on a CloudSim simulation platform, the experimental results show that the algorithm has the advantages of improving optimization and taking less time. So it can be used to research and practice about cloud computing problem for complex scheduling optimization.