Abstract
Grid computing aims to enable “resource sharing and coordinated problem solving in dynamic, multi-institutional virtual organizations (VOs)”. Within the grid computing context, successful dynamic VO formations mean a number of individuals and institutions associated with certain resources join together and form new VOs in order to effectively execute tasks within given time steps. To date, while the concept of VOs has been accepted, few research has been done on the impact of effective dynamic virtual organization formations. In this paper, we develop a performance model of dynamic VOs formation and analyze the effect of different complex organizational structures and their various statistic parameter properties on dynamic VO formations from three aspects: (1) the probability of a successful VO formation under different organizational structures and statistic parameters change, e.g. average degree; (2) the effect of task complexity on dynamic VO formations; (3) the impact of network scales on dynamic VO formations. The experimental results show that the proposed model can be used to understand the dynamic VO formation performance of the simulated organizations. The work provides a good path to understand how to effectively schedule and utilize resources based on the complex grid network and therefore improve the overall performance within grid environment.
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