An efficient resource utilization technique for consolidation of virtual machines in cloud computing environments

Abstract

The problem of migrating virtual machines (VMs) among different physical hosts is vital for resource utilization and carbon dioxide (CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) minimization in cloud data centers. The proposed technique CPU Utilization Variance (CUV) is based on selecting the best VMs from overutilized servers and migrating them into other servers to save the utilized resources and not to violate the Service Level Agreements established between the end users and cloud service provider. CUV also chooses the most appropriate host to allocate these VMs by calculating the minimum variance of all CPU utilization between all physical servers. CUV is implemented in a large-scale data center composed of 800 physical hosts and the results obtained by CloudSim tool in terms of energy consumption in KW/hour, performance in Million Instructions per Second (MIPS), number of VM migrations and Service Level Agreement Violation are reported. Further, a comparative study is performed between CUV and recently researches for evaluating it, which achieved high performance and lower energy consumption without violating the service level agreements in a large-scale data centers.