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Improving Accuracy of Virtual Machine Power Model by Relative-PMC Based Heuristic Scheduling

In: Computing and Informatics, vol. 35, no. 2
P. Xiao - D.b. Liu

Details:

Year, pages: 2016, 241 - 258
Keywords:
Cloud computing, energy efficiency, data center, heuristic algorithm, workflow
About article:
Conventional utilization-based power model is effective for measuring the power consumption of physical machines. However, in virtualized environments its accuracy cannot be guaranteed because of the recursive resource accessing among multiple virtual machines. In this paper, we present a novel virtual machine scheduling algorithm, which uses Performance-Monitor-Counter as heuristic information to compensate the recursive power consumption. Theoretical analysis indicates that the error of virtual machine power model can be quantitative bounded when using the proposed scheduling algorithm. Extensive experiments based on standard benchmarks show that the error of virtual machine power measurements can be significantly reduced comparing with the classic credit-based scheduling algorithm.
How to cite:
ISO 690:
Xiao, P., Liu, D. 2016. Improving Accuracy of Virtual Machine Power Model by Relative-PMC Based Heuristic Scheduling. In Computing and Informatics, vol. 35, no.2, pp. 241-258. 1335-9150.

APA:
Xiao, P., Liu, D. (2016). Improving Accuracy of Virtual Machine Power Model by Relative-PMC Based Heuristic Scheduling. Computing and Informatics, 35(2), 241-258. 1335-9150.