An Optimization VM Deployment for Maximizing Energy Utility in Cloud Environment

With rapid growth of the demand for computation power, which has led to establish plenty of large-scale data centers consuming enormous amount of electrical power. Energy consumption has become a critical problem. We propose an energy efficient multi-dimension resource allocation algorithm for virtualized Cloud datacenters that reduces energy costs and provides required Quality of Service (QoS). Our VM deployment algorithm achieves a good balance between energy and performance by minimizing the amount of provisioning servers as well as maximizing time sharing of VMs hosted on the same server. Energy saving is achieved by VM deployment, continuous consolidation according to current utilization of resources, workload demand and load states of computing nodes. Our scheme achieves a good balance between energy consumption and performance. Meanwhile, we adopt DPS (dynamic powering on/off servers) techniques to power on/off servers and buffer the change of workload, and also adjust consolidation threshold dynamically. The results show that our proposed strategies bring sustainable energy saving while ensuring reliable QoS.