Efficiency Energy Consumption in Cloud Computing Based on Constant Position Selection Policy in Dynamic Virtual Machine Consolidation

Cloud computing is a powerful computation resources that required massive electrical energy. Nowadays, energy efficient become an important issue around the world that leads to the green technology research in cloud computing area. This research focus in efficiently electrical energy consumption in Cloud Computing area especially by improving VM selection policy in dynamic VM consolidation. The procedure of overall strategy Dynamic VM consolidation consist with four basic phase (1) Host overloading detection, (2) VM selection, (3) Host underloading detection, and (4) VM placement. The proposed method in this study focus in VM selection policy, where the idea of the proposed method is by minimalizing the time to select or decide virtual machine in overloaded host that required to migrate constantly based on VMs position. The method is selecting position VMs that will be migrate with constant selection at first, center or last VMs position when overloaded host has been detected with Local Regression algorithm. The performance of proposed method will be evaluate by measures Energy Consumption, SLAV, SLATAH, and FOAM parameter with real-world workload data from PlanetLab VMs. The results of proposed method is showed promising results with improvement energy efficiency and acceptable SLA compare with other VMs selection policy technique.