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Journal of Scheduling

, Volume 14, Issue 3, pp 291–306 | Cite as

Modelling and solving grid resource allocation problem with network resources for workflow applications

  • Marek Mika
  • Grzegorz Waligóra
  • Jan Węglarz
Article

Abstract

A problem of allocating resources of a grid to workflow applications is considered. The problem consists, generally, in allocating distributed grid resources to tasks of a workflow in such a way that the resource demands of each task are satisfied. Grid resources are divided into computational resources and network resources. Computational tasks and transmission tasks of a workflow are distinguished. We present a model of the problem, and an algorithm for finding feasible resource allocations. A numerical example is included, showing the importance of the resource allocation phase on a grid. Some conclusions and directions for future research are given.

Grid Workflow Resource allocation Project scheduling 

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References

  1. Błażewicz, J., Ecker, K., Pesch, E., Schmidt, G., & Węglarz, J. (2001). Scheduling computer and manufacturing processes (2nd ed.). Berlin: Springer. Google Scholar
  2. Błażewicz, J., Ecker, K., Pesch, E., Schmidt, G., & Węglarz, J. (2007). Handbook on scheduling: from theory to applications. Berlin: Springer. Google Scholar
  3. Deelman, E., Blythe, J., Gil, Y., Kesselman, C., Mehta, G., Vahi, K., Blackburn, K., Lazzarini, A., Arbree, A., Cavanaugh, R., & Korranda, S. (2003). Mapping abstract complex workflows onto grid environments. Journal of Grid Computing, 1(1), 25–39. CrossRefGoogle Scholar
  4. Deelman, E., Blythe, J., Gil, Y., Kesselman, C., Mehta, G., Patil, S., Su, M. H., Vahi, K., & Livny, M. (2004). Pegasus: mapping scientific workflows onto the grid. In Proceedings of the 2nd European across grids conference, Nicosia, Cyprus (pp. 11–20). Google Scholar
  5. Deelman, E., Blythe, J., Jain, S., Gil, Y., Vahi, K., Mandal, A., & Kennedy, K. (2005). Task scheduling strategies for workflow-based applications in grids. In Proceedings of the 5th IEEE international symposium on cluster computing and grid, Cardiff, UK (pp. 759–767). Google Scholar
  6. Demeulemeester, E. L., & Herroelen, W. S. (2002). Project scheduling—a research handbook. Boston: Kluwer. Google Scholar
  7. Foster, I., & Kesselman, C. (1999). Computational grids. In I. Foster & C. Kesselman (Eds.), The grid: blueprint for a new computing infrastructure (pp. 15–52). San Mateo: Morgan Kaufmann. Google Scholar
  8. Foster, I., Voeckler, J., Wilde, M., & Zhao, Y. (2002). Chimera: a virtual data system for representing, querying, and automating data derivation. In Proceedings of the 14th conference on scientific and statistical database management, Edinburgh, UK (pp. 37–46). Google Scholar
  9. Józefowska, J., & Węglarz, J. (2006). Perspectives in modern project scheduling. New York: Springer. Google Scholar
  10. Kurowski, K., Nabrzyski, J., & Pukacki, J. (2001). User preference driven multiobjective resource management in grid environments. In Proceedings of cluster computing and the grid conference, 15–18 May 2001, Australia (pp. 114–122). Google Scholar
  11. Kurowski, K., Nabrzyski, J., Oleksiak, A., & Węglarz, J. (2003). Multicriteria aspects of grid resource management. In J. Nabrzyski, J. Schopf & J. Węglarz (Eds.), Grid resource management: state of the art and future trends (pp. 271–293). Boston: Kluwer. Google Scholar
  12. Kurowski, K., Nabrzyski, J., Oleksiak, A., & Węglarz, J. (2006). Grid multicriteria job scheduling with resource reservation and prediction mechanisms. In J. Józefowska & J. Węglarz (Eds.), Perspectives in modern project scheduling (pp. 345–373). New York: Springer. Google Scholar
  13. Kurowski, K., Nabrzyski, J., Oleksiak, A., & Węglarz, J. (2008). Multicriteria approach to two-level hierarchy scheduling in grids. Journal of Scheduling, 11(5), 371–379. CrossRefGoogle Scholar
  14. Leung, J. Y.-T. (2004). Handbook of scheduling: algorithms, models, and performance analysis. London, Boca Raton: Chapman & Hall/CRC. Google Scholar
  15. Mika, M., Waligóra, G., & Węglarz, J. (2003). A metaheuristic approach to scheduling workflow jobs on a grid. In J. Nabrzyski, J. Schopf & J. Węglarz (Eds.), Grid resource management: state of the art and future trends (pp. 295–318). Boston: Kluwer. Google Scholar
  16. Nabrzyski, J., Schopf, J., & Węglarz, J. (2003). Grid resource management: state of the art and future trends. Boston: Kluwer. Google Scholar
  17. Szalay, A. S., Kunszt, P. Z., Thakar, A., Gray, J., Slutz, D., & Brunner, R. J. (2000). Designing and mining multi-terabyte astronomy archives: the Sloan Digital Sky Survey. SIGMOD Record, 29, 451–462. CrossRefGoogle Scholar
  18. Wulz, C.-E. (1998). CMS concept and physics potential. Proceedings of the American Institute of Physics Conference, 444(1), 467–478. Google Scholar
  19. Węglarz, J., Józefowska, J., Mika, M., & Waligóra, G. (2010). Project scheduling with finite or infinite number of activity processing modes—a survey. European Journal of Operational Research (to appear). Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Institute of Computing SciencePoznań University of TechnologyPoznańPoland

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