Title: Energy-performance optimisation for the dynamic consolidation of virtual machines in cloud computing

Authors: H. Li; T. Li; Z. Shuhua

Addresses: School of Science and Technology, Tianjin University of Finance and Economics, Tianjin, China ' School of Science and Technology, Tianjin University of Finance and Economics, Tianjin, China ' Coordinated Innovation Center for Computable Modeling in Management Science, Tianjin University of Finance and Economics, Tianjin, China

Abstract: Dynamic consolidation of virtual machines (VMs) can reduce energy consumption by switching idle hosts to sleep mode. However, to meet the quality of service of customers, it is necessary to achieve the trade-off between energy and performance. This paper first puts forward a new dynamic threshold adjustment method using the variation coefficient of historical CPU utilisation, actual CPU utilisation and million instructions per second requests by VMs in migration list. Furthermore, it devises a novel VM allocation policy based on the grey correlation degree model, and formulates a conversion model of CPU utilisation for achieving better trade-off between energy consumption and performance. Finally, some experiments are carried out on the CloudSim and the PlanetLab workloads. The experimental results show that the methods proposed in this paper have obvious advantages on the trade-off between energy and performance during the VM consolidation.

Keywords: energy and performance optimisation; grey correlation degree; self-adaptive thresholds; VM allocation; VM consolidation.

DOI: 10.1504/IJSOI.2018.088517

International Journal of Services Operations and Informatics, 2018 Vol.9 No.1, pp.62 - 82

Received: 16 Feb 2017
Accepted: 22 Mar 2017
Published online: 11 Dec 2017 *

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