Dynamic Resource Allocation in Distributed Cloud Computing 


Vol. 38,  No. 7, pp. 512-518, Jul.  2013


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  Abstract

A resource allocation algorithm has a high impact on user satisfaction as well as the ability to accommodate and process services in a distributed cloud computing. In other words, service rejections, which occur when datacenters have no enough resources, degrade the user satisfaction level. Therefore, in this paper, we propose a resource allocation algorithm considering the cloud domain’s remaining resources to minimize the number of service rejections. The resource allocation rate based on Q-Learning increases when the remaining resources are sufficient to allocate the maximum allocation rate otherwise and avoids the service rejection. To demonstrate, We compare the proposed algorithm with two previous works and show that the proposed algorithm has the smaller number of the service rejections.

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  Cite this article

[IEEE Style]

T. Ahn, Y. Kim, S. Lee, "Dynamic Resource Allocation in Distributed Cloud Computing," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 7, pp. 512-518, 2013. DOI: .

[ACM Style]

TaeHyoung Ahn, Yena Kim, and SuKyoung Lee. 2013. Dynamic Resource Allocation in Distributed Cloud Computing. The Journal of Korean Institute of Communications and Information Sciences, 38, 7, (2013), 512-518. DOI: .

[KICS Style]

TaeHyoung Ahn, Yena Kim, SuKyoung Lee, "Dynamic Resource Allocation in Distributed Cloud Computing," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 7, pp. 512-518, 7. 2013.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880