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Title:New Worker-Centric Scheduling Strategies for Data-Intensive Grid Applications
Author(s):Ko, Steven Y.; Morales, Ramses V.; Gupta, Indranil
Subject(s):Grid environments
Abstract:In this paper we argue that a worker-centric scheduler design is more desirable for data-intensive applications in Grid environments. Previous research on task-centric scheduling for dataintensive applications has identi ed that reusing the data present in a Grid site improves performance. However, task-centric scheduling bears two problems - unbalanced task assignments and premature scheduling decisions. On the contrary, both of these problems can be avoided by using worker-centric scheduling, thus worker-centric scheduling leads to a simpler scheduler design and better performance. Therefore, we propose a series of workercentric scheduling strategies for data-intensive applications and evaluate, with a real application (Coadd), how each strategy performs compared to a task-centric one. Our results show that worker-centric strategies improve the performance in terms of makespan and bandwidth usage.
Issue Date:2006-05
Genre:Technical Report
Other Identifier(s):UIUCDCS-R-2006-2724
Rights Information:You are granted permission for the non-commercial reproduction, distribution, display, and performance of this technical report in any format, BUT this permission is only for a period of 45 (forty-five) days from the most recent time that you verified that this technical report is still available from the University of Illinois at Urbana-Champaign Computer Science Department under terms that include this permission. All other rights are reserved by the author(s).
Date Available in IDEALS:2009-04-21

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