Resource Allocation in Cloud Environment Using Approaches Based Particle Swarm Optimization

Abstract

It is obvious that in emerging computing paradigms such as cloud computing systems, scheduling is one of the main phases to take advantages of capabilities.The cloud computing environment is a dynamic environment which allows services to be shared among many users.Scheduling methods of traditional systems are ill-suited for the cloud computing systems, and this new environment requires new methods tailored to its specifications.In this paper, we developed multiple algorithms for task scheduling in cloud computing systems.These algorithms are based on the particle swarm optimization (PSO) algorithm, which is a technique inspired by collective and social behavior of animal swarms in nature, and wherein particles search the problem space to find an optimal or near-optimal solution.The algorithms were developed with the aim of minimizing Makespan, Flowtime and the task execution cost simultaneously.Simulation and test results show the better efficiency of the proposed methods than other similar algorithms.