A TASK SCHEDULING APPROACH IN CLOUD COMPUTING TO MINIMIZE THE POWER COST IN DATACENTERS USING CROW SEARCH

Authors

  • sudheer Mangalampalli, Vamsi Krishna Mangalampalli, Sangram Keshari Swain

Abstract

Cloud Computing is evolved as an enormous paradigm in the IT industry. This model enables the users to use the resources in the cloud in the form of services. Task Scheduling is an extensive problem in Cloud computing. To effectively map the tasks onto the suitable virtual machines in the cloud computing a Task scheduler is necessary. Task Scheduler in the cloud computing aimed at minimizing the makespan of the tasks and appropriately map the tasks to the suitable virtual machines. In the literature, many of the authors used evolutionay algorithms to solve the scheduling problem in Cloud Computing. The existing algorithm focuses on the metrics makespan, utilization of the resources. Power for the Datacenters is an important metric in the view of Cloud provider. In the existing algorithms, Power Cost metric at the datacenters was not that much highlighted. In this paper, our focus is to develop a multi objective task scheduling algorithm which schedules the tasks to the appropriate virtual machines by considering the electricity unit cost in datacenters by minimizing the makespan of the tasks and the Power Cost at the Datacenters. We have used Crow Search algorithm to solve the scheduling problem. It is simulated on the CloudSim simulator and it is compared with the existing algorithms ACO, PSO and CS and our approach surpass the existing algorithms in terms of makespan and the Power Cost.

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Published

2020-12-01

How to Cite

sudheer Mangalampalli, Vamsi Krishna Mangalampalli, Sangram Keshari Swain. (2020). A TASK SCHEDULING APPROACH IN CLOUD COMPUTING TO MINIMIZE THE POWER COST IN DATACENTERS USING CROW SEARCH. PalArch’s Journal of Archaeology of Egypt / Egyptology, 17(6), 7201-7212. Retrieved from http://mail.palarch.nl/index.php/jae/article/view/1989