A Virtual Machine Scheduling Method for Trade-offs Between Energy and Performance in Cloud Environment

Cloud computing promises on-demand resource provisioning for customers and it has drawn most attention of academia and industry to accommodate their applications in cloud platforms. Currently, cloud datacenters consume a huge amount of power which has become a big concern worldwide. Live virtual machine (VM) migration provides potential opportunities and probabilities to achieve energy savings. However, it is still a challenge to conduct VM scheduling in energy-efficient and performance-guaranteed manners, since VM migrations bring about both energy conservation and VM performance degradation. In this paper, a VM scheduling method for trade-offs between energy and performance in cloud environment is proposed to address the above challenge. Specifically, a joint optimization model is designed to formalize our problem, then a corresponding energy and performance aware VM scheduling method is proposed to determine which VMs should be migrated and where they should be migrated, aiming at reducing energy consumption and mitigating performance degradation. Simulation results demonstrate that the proposed method is both effective and efficient.