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Sponsored by the Center for Science and Technology Development of the Ministry of Education
Supervised by Ministry of Education of the People's Republic of China
In this paper, an energy-aware method of virtual machines (VM) scheduling in DVFS-enabled cloud is proposed. We define performance-power ratio to weight the physical machines, and the physical machine with high performance-power ratio is assigned to VMs first. VMs are allocated when they arrive, and consolidated every time interval to fully utilize the physical machine with high performance-power ratio. The simulation results show that our scheduling algorithm consumes less energy than existing ones.
Keywords:Virtual Machine Scheduling; Cloud Computing; Dynamic Voltage and Frequency Scaling; Energy Efficiency