QoS Aware Energy Efficient VM Consolidation Techniques for a Virtualized Data Center

Abstract

The large-scale virtualized data centers in the Cloud environment consume huge amount of energy leading to high operational costs and emission of greenhouse gases. Energy consumption of a data center can be reduced by dynamically consolidating the virtual machines (VMs) to a minimum number of physical machines, using live migration. However, the dynamic workload of virtual machines makes the VM consolidation problem more challenging. In this paper, we have proposed a prediction based migration technique for the VMs, where we perform VM migrations based on the predicted CPU utilization. Extensive simulations show that the proposed technique substantially reduces energy consumption, number of VM migrations and Service Level Agreement (SLA) violations within a data center. The performance overheads associated with excessive migration of VMs increase the time needed by the VMs to complete their jobs. So in this paper, we have also proposed a deadline aware VM migration technique, which reduces the time taken by the VMs to execute their jobs significantly, thereby improving the Quality of Service (QoS). Such improvement in QoS is achieved at the cost of slight increase in the energy consumption within the data center. However, simulation results show that appropriate setting of deadlines for the VMs, helps in achieving a trade-off between energy consumption and the QoS.