Job Allocation Strategies with User Run Time Estimates for Online Scheduling in Hierarchical Grids |
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Authors: | Juan Manuel Ram��rez-Alcaraz Andrei Tchernykh Ramin Yahyapour Uwe Schwiegelshohn Ariel Quezada-Pina Jos�� Luis Gonz��lez-Garc��a Ad��n Hirales-Carbajal |
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Affiliation: | 1. Computer Science Department, CICESE Research Center, Ensenada, BC, M??xico 2. Telematics Faculty, Colima University, 28040, Colima, Col., M??xico 3. IT and Media Center, Technische Universit?t Dortmund, 44221, Dortmund, Germany 4. Robotics Research Institute, Technische Universit?t Dortmund, 44221, Dortmund, Germany 5. Science Faculty, Autonomous University of Baja California, Ensenada, 22860, BC, M??xico
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Abstract: | We address non-preemptive non-clairvoyant online scheduling of parallel jobs on a Grid. We consider a Grid scheduling model
with two stages. At the first stage, jobs are allocated to a suitable Grid site, while at the second stage, local scheduling
is independently applied to each site. We analyze allocation strategies depending on the type and amount of information they
require. We conduct a comprehensive performance evaluation study using simulation and demonstrate that our strategies perform
well with respect to several metrics that reflect both user- and system-centric goals. Unfortunately, user run time estimates
and information on local schedules does not help to significantly improve the outcome of the allocation strategies. When examining
the overall Grid performance based on real data, we determined that an appropriate distribution of job processor requirements
over the Grid has a higher performance than an allocation of jobs based on user run time estimates and information on local
schedules. In general, our experiments showed that rather simple schedulers with minimal information requirements can provide
a good performance. |
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