2-phase optimization method for energy aware scheduling of virtual machines in cloud data centers

Need for computational power grows faster and faster so that we have "Cloud Computing" concept emerged from this need. In the other hand with growing popularity of computing and communication, request for more energy power increases and area of Green Computing try to moderate this procedure with revising old computing method or inventing new method to have more efficient computing material that would work more while consuming less energy and making less pollution. In this paper, the researchers tried to reduce energy consumed in Cloud computing datacenters by revising virtual machines scheduling method while keeping quality of service parameters as high as possible. We implemented our approach using CloudSim toolkit and evaluated it in compare with recent popular methods. Evaluation result demonstrates our success in reaching our aims to reduce energy consumption while keeping quality of service in acceptable range by reduction in number of virtual machines migrations.