Abstract
AbstractIn this paper, we propose resource provisioning as the means to reduce the completion time of scientific workflows in a Grid environment. We propose task clustering as a form of workflow optimization that can be used along with provisioning in order to achieve this reduction in completion time. Provisioning can be done statically using advance reservations (ARs) or using dynamic provisioning mechanisms. A simulation is done using the Maui simulator, a workload trace collected from the NCSA Teragrid cluster and 13 workflows to study the effect of provisioning on the completion time of the scientific workflows. The results show in general a reduction of about 50% in the workflow completion time using provisioning for the First In First Out and fair share scheduling policies. In this paper, we also examine the cost of resource provisioning and propose a utilization‐based metric that can be used to guide the provisioning decisions in order to reduce the cost. Finally, we present the results of a survey on the support of AR at the Grid sites. Copyright © 2011 John Wiley & Sons, Ltd.
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