Resource reconstruction algorithms for on-demand allocation in virtual computing resource pool

Authors:
Xiao-Jun Chen;Jing Zhang;Jun-Huai Li;Xiang Li
Affiliations:
School of Computer Science and Engineering, Xi'an University of Technology, Xi'an, PRC 710048;School of Computer Science and Engineering, Xi'an University of Technology, Xi'an, PRC 710048 and State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, PRC ...;School of Computer Science and Engineering, Xi'an University of Technology, Xi'an, PRC 710048;School of Computer Science and Engineering, Xi'an University of Technology, Xi'an, PRC 710048
Venue:
International Journal of Automation and Computing
Year:
2012

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Abstract

Resource reconstruction algorithms are studied in this paper to solve the problem of resource on-demand allocation and improve the efficiency of resource utilization in virtual computing resource pool. Based on the idea of resource virtualization and the analysis of the resource status transition, the resource allocation process and the necessity of resource reconstruction are presented. Resource reconstruction algorithms are designed to determine the resource reconstruction types, and it is shown that they can achieve the goal of resource on-demand allocation through three methodologies: resource combination, resource split, and resource random adjustment. The effects that the resource users have on the resource reconstruction results, the deviation between resources and requirements, and the uniformity of resource distribution are studied by three experiments. The experiments show that resource reconstruction has a close relationship with resource requirements, but it is not the same with current distribution of resources. The algorithms can complete the resource adjustment with a lower cost and form the logic resources to match the demands of resource users easily.