A mission-driven two-step virtual machine commitment for energy saving of modern data centers through UPS and server coordinated optimizations

Guisen Ye, Feng Gao and Jingyang Fang

Applied Energy, 2022, vol. 322, issue C, No S0306261922007942

Abstract: Recent years witness a rapid increasing of data center energy consumption, among which the power losses of uninterruptible power supply (UPS) and server dominate. This paper proposes a mission-driven two-step virtual machine (VM) commitment by considering the characteristics of UPS power losses in virtual machine allocation. To formulate the optimization problem, a power model of data center is built by combining server power with power losses of rack level UPSs. Further, a two-step virtual machine allocation method is proposed, in which the best fit decreasing algorithm first groups the VMs and then the genetic algorithm searches for the optimal allocation of servers equipped with the grouped VMs. A data center with 100 servers and 100 VMs is simulated using the public data collected from PlanetLab platform. Results have verified that the total power consumption is reduced by up to 2.47%. In parallel, possible combinations need to be searched decrease by 3.35 × 10182 times in the VM allocation problem in the case with 100 servers and 100 VMs.

Keywords: Virtual machine; Uninterruptible power supply; Power consumption; Genetic algorithm (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.apenergy.2022.119467

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