On the dynamic resource availability in grids

  • Authors:

  • Alexandru Iosup;Mathieu Jan;Ozan Sonmez;Dick H. J. Epema

  • Affiliations:

  • Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, The Netherlands;LRI/INRIA Futurs, University of Paris South, France;Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, The Netherlands;Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, The Netherlands

  • Venue:
  • GRID '07 Proceedings of the 8th IEEE/ACM International Conference on Grid Computing
  • Year:
  • 2007

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Abstract

Currently deployed grids gather together thousands of computational and storage resources for the benefit of a large community of scientists. However, the large scale, the wide geographical spread, and at times the decision of the rightful resource owners to commit the capacity elsewhere, raises serious resource availability issues. Little is known about the characteristics of the grid resource availability, and of the impact of resource unavailability on the performance of grids. In this work, we make first steps in addressing this twofold lack of information. First, we analyze a long-term availability trace and assess the resource availability characteristics of Grid’5000, an experimental grid environment of over 2,500 processors. The average utilization for the studied trace is increased by almost 5%, when availability is considered. Based on the results of the analysis, we further propose a model for grid resource availability. Our analysis and modeling results show that grid computational resources become unavailable at a high rate, negatively affecting the ability of grids to execute long jobs. Second, through trace-based simulation, we show evidence that resource availability can have a severe impact on the performance of the grid systems. The results of this step show evidence that the performance of a grid system can rise when availability is taken into consideration, and that human administration of availability change information results in 10–15 times more job failures than for an automated monitoring solution, even for a lowly utilized system.