Title: An energy-efficient adaptive resource provision framework for cloud platforms

Authors: Dongbo Liu; Peng Xiao

Addresses: Department of Computer, Hunan Institute of Engineering, Xiangtan City, China ' Department of Computer, Hunan Institute of Engineering, Xiangtan City, China

Abstract: In cloud computing, resource provision service plays an important role for operating large-scale datacentres. Conventional resource provision policies or services mainly concentrate on optimising costs and application execution performance. In this paper, we present an integrated and adaptive resource provision framework, which is based on our previous work on performance monitor in cloud environments. In the proposed framework, several novel mechanisms are implemented, aiming at improving the energy-efficiency as well as the execution performance for cloud systems. Extensive experiments are conducted to evaluate the performance of the proposed framework in terms of different metrics. The experimental results show that the proposed framework can significantly improve the energy-efficiency metric, especially when a cloud system is in presence of intensive hybrid workloads.

Keywords: cloud computing; energy efficiency; quality of service; QoS; virtual machines; data centres; adaptive resource provision; cloud resources; energy consumption.

DOI: 10.1504/IJCSE.2016.080211

International Journal of Computational Science and Engineering, 2016 Vol.13 No.4, pp.346 - 354

Received: 05 Aug 2014
Accepted: 23 Nov 2014

Published online: 04 Nov 2016 *

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