Optimum Utilization of Resources Through Restricted Virtual Machine Migration and Efficient VM Placement in Cloud Data Center

Abstract

In infrastructure-as-a-service (IAAS) cloud platforms, it is a real challenge to provide high performance gain by the optimum utilization of resources while maintaining minimum consumption of energy. The existing research works show that reduction in energy consumption causes violation of service level agreement (SLA). In this article, the concept of probability has been used to take the migration decision of virtual machines (VM) from over-utilized as well as under-utilized nodes. A novel method has also been proposed for selecting the destination server where a migrated VM will be placed. This method is based on the current utilization of CPU, memory and network bandwidth. The proposed scheme maintains a balance between energy consumption and performance gain. Results obtained through trace driven simulation demonstrate that the probability-based migration scheme achieves energy-performance trade-off whereas the VM placement method shows a very high gain in performance.