Skip to main content
Log in

Supporting schedules of resource co-allocation for distributed computing in scalable systems

  • Published:
Programming and Computer Software Aims and scope Submit manuscript

Abstract

This paper proposes a model of scheduling and validates methods of resource co-allocation for distributed computations in scalable systems. Solution of the problem of allocating heterogeneous computing resources for performing complex sets of tasks (jobs) is related to the formation of strategies (families of admissible supporting schedules). The choice of a specific schedule depends on the nature of events occurring in the distributed environment and related primarily to the load and accessibility of computing nodes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Teoriya raspisanii i vychislitel’nye mashiny (Scheduling Theory and Computers), Koffman, E.G., Ed., Moscow: Nauka, 1984.

    Google Scholar 

  2. Mikhalevich, V.S. and Kuksa, A.I., Metody posledovatel’noi optimizatsii v diskretnykh setevykh zadachakh optimal’nogo raspredeleniya resursov (Methods of Sequential Optimization in Discrete Network Problems of Optimal Resource Distribution), Moscow: Nauka, 1983.

    Google Scholar 

  3. Casavant, T.L. and Kuhl, J.G., A Taxonomy of Scheduling in General-Purpose Distributed Computing Systems, IEEE Trans. Software Eng., 1988, vol. 14, no. 2, pp. 141–154.

    Article  Google Scholar 

  4. Czajkowski, K., Foster, I., and Kesselman, C., Resource Co-Allocation in Computational Grids, Proc. of the 8th IEEE Symp. on High-Performance Distributed Computing (HPDC-8), 1999, pp. 219–228.

  5. Kovalenko, V.N. and Koryagin, D.A., Organization of Grid Resources, Preprint no. 63 of the Keldysh IPM RAS, Moscow: 2004.

  6. Toporkov, V.V., Modeli raspredelennykh vychislenii (Models of Distributed Computing), Moscow: Fizmatlit, 2004.

    Google Scholar 

  7. Toporkov, V.V., Strategies for Scheduling of Distributed Computing in Scalable Systems: Methods and Tools for Information Processing, Proc. of the First All-Russian Scientific Conference, pp. 509–514, Moscow: MSU, 2003.

    Google Scholar 

  8. Natrajan, A., Humphrey, M.A., and Grimshaw, A.S., Grid Resource Management in Legion, Grid Resource Management. State of the Art and Future Trends, Nabrzyski, J., Schopf, J.M., and Weglarz, J., Eds., Kluwer, 2003, pp. 145–160.

  9. Kurowski, K., Nabrzyski, J., Oleksiak, A., et al., Multicriteria Aspects of Grid Resource Management, Grid Resource Management. State of the Art and Future Trends, Nebrzyski, J., Schopf, J.M., and Weglarz, J., Eds., Kluwer, 2003, pp. 271–293.

  10. Shao, G., Wolski, R., and Berman, F., Performance Effects of Scheduling Strategies for Master/Slave Distributed Applications, UCSD CSE Tech. Rep. no. CS98-598, San Diego: Univ. of California, 1998, http://wwwcse.ucsd.edu/users/berman/apples.html

    Google Scholar 

  11. Yang, L., Schopf, J.M., and Foster, I., Conservative Scheduling: Using Predicted Variance to Improve Scheduling Decisions in Dynamic Environments, Supercomputing, 2003, Nov., http://www.globus.org/alliance/publications/papers.

  12. Ranganathan, K. and Foster, I., Decoupling Computation and Data Scheduling in Distributed Data-Intensive Applications, Proc. of the 11th IEEE Symp. on High-Performance Distributed Computing (HPDC-11), Scotland, 2002, http://www.globus.org/alliance/publications/papers

  13. Kiselev, A., Korneev, V., Semenov, D., et al., Management of Metacomputer Systems, Otkrytye systemy, 2005, vol. 32, pp. 11–16.

    Google Scholar 

  14. Buyya, R., Abramson, D., Giddy, J., et al., Economic Models for Resource Management and Scheduling in Grid Computing, J. Concurrency and Computation: Practice and Experience, 2002, May, http://www.buyya.com/papers

  15. Berezovskii, P.S. and Kovalenko, V.N., Policy of Resource Allocation in Grid, Proc. of Int. Conf. “Distributed Computing and Grid-Technologies in Science and Education”, Dubna, June 29–July 2, 2004, Dubna: JINR, 2004, pp. 36–41.

    Google Scholar 

  16. Smith, W., Improving Resource Selection and Scheduling Using Predictions, Grid Resource Management. State of the Art and Future Trends, Nabrzyski, J., Schopf, J.M., and Weglarz, J., Eds., Kluwer, 2003, pp. 237–254.

  17. Toporkov, V.V., Selection of Composition and Distribution of Resources of Real-Time Computing Systems, Avtom. Telemekh., 2005, no. 1, pp. 171–189.

  18. Avetisyan, A.I., Gaisaryan, S.S., and Samovarov, O.I., Possibilities of Optimal Execution of Parallel Programs Containing Simple and Iterated Loops on Heterogeneous Parallel Computational Systems with Distributed Memory, Programmirovanie, 2002, vol. 28, no. 1, pp. 38–54 [Programming Comput. Software (Engl. Transl.), 2002, vol. 28, no. 1, pp. 28–40].

    MathSciNet  Google Scholar 

  19. Toporkov, V. V., Satisfiability of Dataflow Models of Distributed Programs, Programmirovanie, 2001, vol. 27, no. 5, pp. 18–25 [Programming Comput. Software (Engl. Transl.), 2001, vol. 27, no. 5, pp. 238–244].

    MathSciNet  Google Scholar 

  20. Toporkov, V. V., Decidability of the Analysis Problem for Dataflow Models of Programs, Programmirovanie, 2003, vol. 29, no. 3, pp. 3–14 [Programming Comput. Software (Engl. Transl.), 2003, vol. 29, no. 3, pp. 121–129].

    MathSciNet  Google Scholar 

  21. Toporkov, V. V. and Toporkova, A. S., Measuring the Execution Time of Fragmented Programs, Programmirovanie, 2005, vol. 31, no. 3, pp. 19–32 [Programming Comput. Software (Engl. Transl.), 2005, vol. 31, no. 3, pp. 123–132].

    Google Scholar 

  22. Yudin, D. B., Vychislitel’nye metody teorii prinyatiya reshenii (Computational Methods of the Theory of Decision Making), Moscow: Nauka, 1980.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to V. V. Toporkov.

Additional information

Original Russian Text © V.V. Toporkov, 2008, published in Programmirovanie, 2008, Vol. 34, No. 3.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Toporkov, V.V. Supporting schedules of resource co-allocation for distributed computing in scalable systems. Program Comput Soft 34, 160–172 (2008). https://doi.org/10.1134/S0361768808030043

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0361768808030043

Keywords

Navigation