• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/
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Grouping Method based on Adaptive Load Balancing for the Intelligent Resource Management of a Cloud System


Romeo Mark A. Mateo, Hyun-Ho Yang, Jae-Wan Lee, Journal of Internet Computing and Services, Vol. 12, No. 3, pp. 37-48, Jun. 2011
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Keywords: Cloud computing, intelligent framework, cluster analysis, adaptive load balancing

Abstract

Current researches in the Cloud focus on the appropriate interactions of cloud components in a large-scale system implementation. However, the current designs do not include intelligent methods like grouping the similar service providers based on their properties and integrating adaptive schemes for load distribution which can promote effective sharing of resource. This paper proposes an efficient virtualization of services by grouping the cloud providers to improve the service provisioning. The grouping of cloud service providers based on a cluster analysis collects the similar and related services in one group. The adaptive load balancing supports the service provisioning of the cloud system where it manages the load distribution within the group using an adaptive scheme. The proposed virtualization mechanism (GRALB) showed good results in minimizing message overhead and throughput performance compared to other methods.


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Cite this article
[APA Style]
Mateo, R., Yang, H., & Lee, J. (2011). Grouping Method based on Adaptive Load Balancing for the Intelligent Resource Management of a Cloud System. Journal of Internet Computing and Services, 12(3), 37-48.

[IEEE Style]
R. M. A. Mateo, H. Yang, J. Lee, "Grouping Method based on Adaptive Load Balancing for the Intelligent Resource Management of a Cloud System," Journal of Internet Computing and Services, vol. 12, no. 3, pp. 37-48, 2011.

[ACM Style]
Romeo Mark A. Mateo, Hyun-Ho Yang, and Jae-Wan Lee. 2011. Grouping Method based on Adaptive Load Balancing for the Intelligent Resource Management of a Cloud System. Journal of Internet Computing and Services, 12, 3, (2011), 37-48.