Energy Efficient VM Live Migration and Allocation at Cloud Data Centers

Aiming at data center virtual machines Migration, allocating resource dynamically in order to reduce energy is a significant problem in cloud. This energy doesn't cause only the decrease of cloud provider's profit but also emit a large amount of carbon dioxide. This paper studies the resource allocation and live migration of Virtual Machines (VMs). It proposes a Double Threshold Migration (DTM) algorithm which takes into consideration an upper and a lower threshold of CPU utilization. These Thresholds let one select a number of VMs to do the migration. The live migration of the VMs reduces the high utilization of the servers and set on off state the unused physical machines (PMs). To solve the problem of the VM placement, the work applies a modification of the Best Fit Decreasing (MBFD) algorithm. Experiment results show that the proposed approach improve resource utilization, reduce the energy consumption and maintain the SLA (Service Level Agreement) violations with the energy constraint.