PSO-COGENT: Cost and energy efficient scheduling in cloud environment with deadline constraint

Abstract

The main goal of cloud service provider is to maximize the profit from cloud infrastructure, while cloud users want to execute their applications in minimum execution cost and time. The rapid growth in demand of computational power invites the massive growth in cloud data centers and requirement of large amount of energy consumption in cloud data centers, becomes a serious threat to the environment. To reduce the energy consumption and gain the maximum profit in cloud environment is a challenging problem due to incompatibility between workstation (physical machine) and unpredictable user demand. In this paper, we have proposed a resource allocation model for processing the applications efficiently and Particle Swarm Optimization based scheduling (PSO) algorithm named as PSO-COGENT algorithm that not only optimize execution cost and time but also reduces the energy consumption of cloud data centers, considering deadline as constraint. The developed PSO-COGENT algorithm has been simulated at cloudsim and observed that it reduces the execution time, execution cost, task rejection ratio, energy consumption and increase the throughput in comparison to PSO, honey bee and min-min algorithm.