Energy aware scheduling using genetic algorithm in cloud data centers

Abstract

Cloud computing is a sophisticated technology which provides services to the end users within a fraction of time based on a pay-as-you-go model. However, energy consumption is one of the important concerns in cloud environment as large amount of energy is wasted by the data centers, hosting cloud applications and the carbon dioxide gas is released into the atmosphere polluting the environment. So pollution needs to be reduced by lowering the energy usage. Therefore, we'd prefer to propose a green computing solution which is not only able to minimize makespan and operational costs however in addition to minimize the environmental pollution. In this paper, we tend to stipulate a framework that specifies energy minimization is a generalization of makespan minimized by using the Energy-Aware Task Scheduler using Genetic Algorithm. We tried to conduct a survey on different scheduling methods of energy minimization in cloud data centers and their limitations and at the end of this paper, we render a green optimized energy-aware task scheduling algorithm for Cloud data centers.