• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Energy-aware Multi-dimensional Resource Allocation Algorithm in Cloud Data Center

Vol. 11, No. 9, September 29, 2017
10.3837/tiis.2017.09.008, Download Paper (Free):

Abstract

Energy-efficient virtual resource allocation algorithm has become a hot research topic in cloud computing. However, most of the existing allocation schemes cannot ensure each type of resource be fully utilized. To solve the problem, this paper proposes a virtual machine (VM) allocation algorithm on the basis of multi-dimensional resource, considering the diversity of user’s requests. First, we analyze the usage of each dimension resource of physical machines (PMs) and build a D-dimensional resource state model. Second, we introduce an energy-resource state metric (PAR) and then propose an energy-aware multi-dimensional resource allocation algorithm called MRBEA to allocate resources according to the resource state and energy consumption of PMs. Third, we validate the effectiveness of the proposed algorithm by real-world datasets. Experimental results show that MRBEA has a better performance in terms of energy consumption, SLA violations and the number of VM migrations.


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Cite this article

[IEEE Style]
J. Nie, J. Luo and L. Yin, "Energy-aware Multi-dimensional Resource Allocation Algorithm in Cloud Data Center," KSII Transactions on Internet and Information Systems, vol. 11, no. 9, pp. 4320-4333, 2017. DOI: 10.3837/tiis.2017.09.008.

[ACM Style]
Jiawei Nie, Juan Luo, and Luxiu Yin. 2017. Energy-aware Multi-dimensional Resource Allocation Algorithm in Cloud Data Center. KSII Transactions on Internet and Information Systems, 11, 9, (2017), 4320-4333. DOI: 10.3837/tiis.2017.09.008.

[BibTeX Style]
@article{tiis:21546, title="Energy-aware Multi-dimensional Resource Allocation Algorithm in Cloud Data Center", author="Jiawei Nie and Juan Luo and Luxiu Yin and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2017.09.008}, volume={11}, number={9}, year="2017", month={September}, pages={4320-4333}}