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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: © 2015 |Pages: 15
ISBN13: 9781466665392|ISBN10: 1466665394|EISBN13: 9781466665408
DOI: 10.4018/978-1-4666-6539-2.ch105
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MLA

Lin, Wei-Wei, et al. "Novel Resource Allocation Algorithm for Energy-Efficient Cloud Computing in Heterogeneous Environment." Cloud Technology: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2015, pp. 2225-2239. https://doi.org/10.4018/978-1-4666-6539-2.ch105

APA

Lin, W., Tan, L., & Wang, J. Z. (2015). Novel Resource Allocation Algorithm for Energy-Efficient Cloud Computing in Heterogeneous Environment. In I. Management Association (Ed.), Cloud Technology: Concepts, Methodologies, Tools, and Applications (pp. 2225-2239). IGI Global. https://doi.org/10.4018/978-1-4666-6539-2.ch105

Chicago

Lin, Wei-Wei, Liang Tan, and James Z. Wang. "Novel Resource Allocation Algorithm for Energy-Efficient Cloud Computing in Heterogeneous Environment." In Cloud Technology: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 2225-2239. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-6539-2.ch105

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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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