Efficiency Sustainability Resource Visual Simulator for Clustered Desktop Virtualization Based on Cloud Infrastructure

Jong Hyuk Park, Hyun-Woo Kim and Young-Sik Jeong
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Jong Hyuk Park: Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul 139-743, Korea
Hyun-Woo Kim: Department of Multimedia Engineering, Dongguk University, Seoul 100-715, Korea
Young-Sik Jeong: Department of Multimedia Engineering, Dongguk University, Seoul 100-715, Korea

Sustainability, 2014, vol. 6, issue 11, 1-13

Abstract: Following IT innovations, manual operations have been automated, improving the overall quality of life. This has been possible because an organic topology has been formed among many diverse smart devices grafted onto real life. To provide services to these smart devices, enterprises or users use the cloud. Cloud services are divided into infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS). SaaS is operated on PaaS, and PaaS is operated on IaaS. Since IaaS is the foundation of all services, algorithms for the efficient operation of virtualized resources are required. Among these algorithms, desktop resource virtualization is used for high resource availability when existing desktop PCs are unavailable. For this high resource availability, clustering for hierarchical structures is important. In addition, since many clustering algorithms show different percentages of the main resources depending on the desktop PC distribution rates and environments, selecting appropriate algorithms is very important. If diverse attempts are made to find algorithms suitable for the operating environments’ desktop resource virtualization, huge costs are incurred for the related power, time and labor. Therefore, in the present paper, a desktop resource virtualization clustering simulator (DRV-CS), a clustering simulator for selecting clusters of desktop virtualization clusters to be maintained sustainably, is proposed. The DRV-CS provides simulations, so that clustering algorithms can be selected and elements can be properly applied in different desktop PC environments through the DRV-CS.

Keywords: desktop resource virtualization; clustering; clustering simulator; cloud computing; infrastructure as a service; clustering visualization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2014
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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