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Scheduling Workflows with Budget Constraints

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Abstract

Grids are emerging as a promising solution for resource and computation demanding applications. However, the heterogeneity of resources in Grid computing, complicates resource management and scheduling of applications. In addition, the commercialization of the Grid requires policies that can take into account user requirements, and budget considerations in particular. This paper considers a basic model for workflow applications modelled as Directed Acyclic Graphs (DAGs) and investigates heuristics that allow to schedule the nodes of the DAG (or tasks of a workflow) onto resources in a way that satisfies a budget constraint and is still optimized for overall time. Two different approaches are implemented, evaluated and presented using four different types of basic DAGs.

This work was supported by the CoreGRID European Network of Excellence, part of the European Commission’s IST programme #004265

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References

  1. O. Beaumont, V. Boudet, and Y. Robert. A realistic model and an efficient heuristic for scheduling with heterogeneous processors. In 11th Heterogeneous Computing Workshop, 2002.

    Google Scholar 

  2. J. Blythe, S. Jain, E. Deelman, Y. Gil, K. Vahi, A. Mandal, and K. Kennedy. Resource Allocation Strategies for Workflows in Grids In IEEE International Symposium on Cluster Computing and the Grid (CCGrid 2005).

    Google Scholar 

  3. R. Buyya, D. Abramson, and S. Venugopal. The Grid Economy. In Proceedings of the IEEE, volume 93(3), pages 698–714, March 2005.

    Article  Google Scholar 

  4. R. Buyya. Economic-based Distributed Resource Management and Scheduling for Grid Computing. PhD thesis, Monash University, Melbourne, Australia, http://www.buyya.com/thesis, April 12 2002.

    Google Scholar 

  5. R. Buyya, D. Abramson, and J. Giddy. An economy grid architecture for service-oriented grid computing. In 10th IEEE Heterogeneous Computing Workshop (HCW’01), San Fran-sisco, 2001.

    Google Scholar 

  6. C. Ernemann, V. Hamscher and R. Yahyapour. Economic Scheduling in Grid Computing. In Proceedings of the 8th Workshop on Job Scheduling Strategies for Parallel Processing, Vol. 2537 of Lecture Notes in Computer Science, Springer, pages 128–152, 2002.

    Google Scholar 

  7. A. Mandal, K. Kennedy, C. Koelbel, G. Marin, J. Mellor-Crummey, B. Liu and L. Johnsson. Scheduling Strategies for Mapping Application Workflows onto the Grid. In IEEE International Symposium on High Performance Distributed Computing (HPDC 2005), 2005.

    Google Scholar 

  8. R. Sakellariou and H. Zhao. A hybrid heuristic for DAG scheduling on heterogeneous systems. In 13th IEEE Heterogeneous Computing Workshop (HCW’04), Santa Fe, New Mexico, USA, April 2004.

    Google Scholar 

  9. R. Sakellariou and H. Zhao. A low-cost rescheduling policy for efficient mapping of workflows on grid systems. In Scientific Programming, volume 12(4), pages 253–262, December 2004.

    Google Scholar 

  10. H. Topcuoglu, S. Hariri, and M. Wu. Performance-effective and low-complexity task scheduling for heterogeneous computing. In IEEE Transactions on Parallel and Distributed Systems, volume 13(3), pages 260–274, March 2002.

    Article  Google Scholar 

  11. L. Wang, H. J. Siegel, V. P. Roychowdhury, and A. A. Maciejewski. Task matching and scheduling in heterogeneous computing environments using a genetic-algorithm-based approach. Journal of Parallel and Distributed Computing, 47:8–22, 1997.

    Article  Google Scholar 

  12. M. Wieczorek, R. Prodan and T. Fahringer. Scheduling of Scientific Workflows in the ASKALON Grid Environment. In SIGMOD Record, volume 34(3), September 2005.

    Google Scholar 

  13. H. Zhao and R. Sakellariou. An experimental investigation into the rank function of the heterogeneous earliest finish time scheduling algorithm. In Euro-Par 2003. Springer-Verlag, LNCS 2790, 2003.

    Google Scholar 

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Sakellariou, R., Zhao, H., Tsiakkouri, E., Dikaiakos, M.D. (2007). Scheduling Workflows with Budget Constraints. In: Gorlatch, S., Danelutto, M. (eds) Integrated Research in GRID Computing. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-47658-2_14

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  • DOI: https://doi.org/10.1007/978-0-387-47658-2_14

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-387-47656-8

  • Online ISBN: 978-0-387-47658-2

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