Job Allocation Strategies with User Run Time Estimates for Online Scheduling in Hierarchical Grids

  • Authors:

  • Juan Manuel Ramírez-Alcaraz;Andrei Tchernykh;Ramin Yahyapour;Uwe Schwiegelshohn;Ariel Quezada-Pina;José Luis González-García;Adán Hirales-Carbajal

  • Affiliations:

  • Computer Science Department, CICESE Research Center, Ensenada, México and Telematics Faculty, Colima University, Colima, México 28040;Computer Science Department, CICESE Research Center, Ensenada, México;IT and Media Center, Technische Universität Dortmund, Dortmund, Germany 44221;Robotics Research Institute, Technische Universität Dortmund, Dortmund, Germany 44221;Computer Science Department, CICESE Research Center, Ensenada, México;Computer Science Department, CICESE Research Center, Ensenada, México;Computer Science Department, CICESE Research Center, Ensenada, México and Science Faculty, Autonomous University of Baja California, Ensenada, México 22860

  • Venue:
  • Journal of Grid Computing
  • Year:
  • 2011

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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.