Performance-to-Power Ratio Aware Virtual Machine (VM) Allocation in Energy-Efficient Clouds

The last decade witnesses a dramatic advance of cloud computing research and techniques. One of the key faced challenges in this field is how to reduce the massive amount of energy consumption in cloud computing data centers. To address this issue, many power-aware virtual machine (VM) allocation and consolidation approaches are proposed to reduce energy consumption efficiently. However, most of those existing efficient cloud solutions save energy cost at a price of the significant performance degradation. In this paper, we present a novel VM allocation algorithm called "PPRGear", which leverages the Performance-to-Power ratios for various host types. By achieving the optimal balance between host utilization and energy consumption, PPRGear is able to guarantee that host computers run at the most power-efficient levels (i.e., the levels with highest Performance-to-Power ratios) so that the energy consumption can be tremendously reduced with little sacrifice of performance. Our extensive experiments with real world traces show that compared with three baseline energy-efficient VM allocation and selection algorithms, PPRGear is able to reduce the energy consumption up to 69.31% for various host computer types with fewer migration and shutdown times and little performance degradation for cloud computing data centers.