VM consolidation approach based on heuristics fuzzy logic, and migration control

To meet the increasing demand of computational power, at present IT service providers' should choose cloud based services for its flexibility, reliability and scalability. More and more datacenters are being built to cater customers' need. However, the datacenters consume large amounts of energy, and this draws negative attention. To address those issues, researchers propose energy efficient algorithms that can minimize energy consumption while keeping the quality of service (QoS) at a satisfactory level. Virtual Machine consolidation is one such technique to ensure energy-QoS balance. In this research, we explore fuzzy logic and heuristic based virtual machine consolidation approach to achieve energy-QoS balance. A Fuzzy VM selection method is proposed in this research. It selects VM from an overloaded host. Additionally, we incorporate migration control in Fuzzy VM selection method that will enhance the performance of the selection strategy. A new overload detection algorithm has also been proposed based on mean, median and standard deviation of utilization of VMs. We have used CloudSim toolkit to simulate our experiment and evaluate the performance of the proposed algorithm on real-world work load traces of Planet lab VMs. Simulation results demonstrate that the proposed method is most energy efficient compared to others.