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Novel Resource Allocation Algorithm for Energy-Efficient Cloud Computing in Heterogeneous Environment

Novel Resource Allocation Algorithm for Energy-Efficient Cloud Computing in Heterogeneous Environment

Wei-Wei Lin, Liang Tan, James Z. Wang
Copyright: © 2014 |Volume: 6 |Issue: 1 |Pages: 14
ISSN: 1938-0259|EISSN: 1938-0267|EISBN13: 9781466654433|DOI: 10.4018/ijghpc.2014010104
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MLA

Lin, Wei-Wei, et al. "Novel Resource Allocation Algorithm for Energy-Efficient Cloud Computing in Heterogeneous Environment." IJGHPC vol.6, no.1 2014: pp.63-76. http://doi.org/10.4018/ijghpc.2014010104

APA

Lin, W., Tan, L., & Wang, J. Z. (2014). Novel Resource Allocation Algorithm for Energy-Efficient Cloud Computing in Heterogeneous Environment. International Journal of Grid and High Performance Computing (IJGHPC), 6(1), 63-76. http://doi.org/10.4018/ijghpc.2014010104

Chicago

Lin, Wei-Wei, Liang Tan, and James Z. Wang. "Novel Resource Allocation Algorithm for Energy-Efficient Cloud Computing in Heterogeneous Environment," International Journal of Grid and High Performance Computing (IJGHPC) 6, no.1: 63-76. http://doi.org/10.4018/ijghpc.2014010104

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Abstract

Energy efficiency is one of the most important design considerations for a cloud data center. Recent approaches to the energy-efficient resource management for data centers usually model the problem as a bin packing problem with the goal of minimizing the number of physical machines (PMs) employed. However, minimizing the number of PMs may not necessarily minimize the energy consumption in a heterogeneous cloud environment. To address the problem, this paper models the resource allocation problem in a heterogeneous cloud data center as a constraint satisfaction problem (CSP). By solving this constraint satisfaction problem, an optimal resource allocation scheme, which includes a virtual machine provision algorithm and a virtual machine packing algorithm, is designed to minimize the energy consumption in a virtualized heterogeneous cloud data center. Performance studies show that this proposed new scheme outperforms the existing bin-packing based approaches in terms of energy consumption in heterogeneous cloud data centers.

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