Research Area:  Cloud Computing
An important issue of energy efficiency in cloud environment is to perform more jobs while consuming less amount of power. Virtual machine consolidation remains the most deployed strategy to manage both performance and energy consumption. Most of existing energy efficiency techniques save energy against the cost on performance degradation. Consolidation techniques leverage thresholds to detect overloaded and underloaded hosts that could be vacated to achieve optimal balance between host utilization and energy consumption. In this research, we propose an energy-efficient strategy (EES) to consolidate virtual machines in cloud environment with an aim of reducing the energy consumption while completing more tasks with the highest throughput. Our proposal makes use of the performance-to-power ratio to set upper thresholds for overload detection. In addition, EES considers the overall data center workload utilization to set lower thresholds, which can reduce the number of virtual machine migrations. The simulation results show that EES leads to energy-efficient workload consolidation with the minimal number of migrations and less energy consumption. The results conclude that EES saves energy consumption without compromising users workload requirement.
Author(s) Name:  Youssef Saadi & Said El Kafhali
Journal name:  Soft Computing
Publisher name:  Springer
Volume Information:  volume 24, pages 14845–14859 (2020)
Paper Link:   https://link.springer.com/article/10.1007/s00500-020-04839-2