Volume 18, No. 6, 2021
Workflow Scheduling Using Energy Aware Makes Pan Minimization Mechanism In Cloud Computing
Chaya T D , Dr. Mohamed Rafi
Abstract
Cloud computing provides the flexible and on-demand business environment based on the resource sharing phenomena to make the service easily available for public utility. Moreover in recent years, workflow scheduling has been one of the prominent cloud computing application; workflow comprises repeated business activity pattern which needs to execute in accordance with sequential checklist. Moreover workflow scheduling requires efficient QoS such as energy consumption, task execution time are important parameter; in past several researcher focused on achieving better performance, however main drawback of these model lies with their efficiency. Hence, in this research we develop an efficient workflow mechanism named EAMM (Energy Aware Makes pan Minimization) to achieve the better performance in workflow scheduling. At first EAMM mechanism designs the problem of processing delay and execution time as a joint problem and solves through the same algorithm. Further this research work focuses on minimizing the make span and energy consumption in VM scheduling. Moreover this is achieved through reducing the execution time on given local processor through designed algorithm. Further EAMM is evaluated by considering the dataset of scientific workflow based Montage and through the comparative analysis it is observed that EAMM simply outperforms the existing model in terms of total execution time and energy consumption.
Pages: 1389-1408
Keywords: Energy Consumption, Makes pan, task execution, EAMM