Advertisement

Job Ranking and Scheduling in Utility Grids VOs

  • Victor ToporkovEmail author
  • Anna Toporkova
  • Alexey Tselishchev
  • Dmitry Yemelyanov
  • Petr Potekhin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9251)

Abstract

In this work, we propose approaches to creation of a ranked jobs framework within a model of cycle scheduling in virtual organizations of utility Grids with the decoupling of users from resource providers. Two methods for job selection and scheduling are proposed and compared: the first one is based on the knapsack problem solution, while the second one introduces a heuristic parameter of a job and a computational resource set “compatibility”. Along with these methods we present experimental results demonstrating the efficiency of proposed approaches and compare them with random job selection.

Keywords

Grid Virtual organization Scheduling Resource management Job Flow Batch Knapsack problem 

Notes

Acknowledgements

This work was partially supported by the Council on Grants of the President of the Russian Federation for State Support of Young Scientists and Leading Scientific Schools (grants YPhD-4148.2015.9 and SS-362.2014.9), RFBR (grants 15-07-02259 and 15-07-03401), the Ministry on Education and Science of the Russian Federation, task no. 2014/123 (project no. 2268), and by the Russian Science Foundation (project no. 15-11-10010).

References

  1. 1.
    Garg, S.K., Konugurthi, P., Buyya, R.: A linear programming-driven genetic algorithm for metascheduling on utility grids. J Par., Emergent and Distr. Systems 26, 493–517 (2011)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Cafaro, M., Mirto, M., Aloisio, G.: Preference-based matchmaking of grid resources with cp-nets. J. Grid Comput. 11(2), 211–237 (2013)CrossRefGoogle Scholar
  3. 3.
    Buyya, R., Abramson, D., Giddy, J.: Economic models for resource management and scheduling in grid computing. J. Concurrency Comput. 14(5), 1507–1542 (2002)CrossRefzbMATHGoogle Scholar
  4. 4.
    Toporkov, V.V., Yemelyanov, D.M.: Economic model of scheduling and fair resource sharing in distributed computations. J. Program. Comput. Softw. 40(1), 35–42 (2014)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Ernemann, C., Hamscher, V., Yahyapour, R.: Economic scheduling in grid computing. In: Feitelson, D.G., Rudolph, L., Schwiegelshohn, U. (eds.) JSSPP 2002. LNCS, vol. 2537, pp. 128–152. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  6. 6.
    Mutz, A., Wolski, R., Brevik, J.: Eliciting honest value information in a batch-queue environment. In: 2007 8th IEEE/ACM International Conference on Grid Computing, pp. 291–297. IEEE Computer Society (2007)Google Scholar
  7. 7.
    Berman, F., Wolski, R., Casanova, H., et al.: Adaptive computing on the grid using appLeS. J. IEEE Trans. On Parallel Distrib. Syst. 14(4), 369–382 (2003)CrossRefGoogle Scholar
  8. 8.
    Cirne, W., Brasileiro, F., Costa, L. et al.: Scheduling in bag-of-task grids: the PAUÁ case. In: 16th Symposium on Computer Architecture and High Performance Computing, pp. 124–131. IEEE (2004)Google Scholar
  9. 9.
    Voevodin, V.: The solution of large problems in distributed computational media. J. Autom. Remote Control 68(5), 773–786 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Dail, H., Sievert, O., Berman, F., et al.: Scheduling in the grid application development software project. In: Nabrzyski, J., Schopf, J.M., Weglarz, J. (eds.) Grid resource management, pp. 73–98. State of the Art and Future Trends. Kluwer Academic Publishers, Dordrecht (2003)Google Scholar
  11. 11.
    Kurowski, K., Oleksiak, A., Nabrzyski, J., et al.: Multi-criteria grid resource management using performance prediction techniques. In: Gorlatch, S., Danelutto, M. (eds.) JSSPP 2010, pp. 215–225. Springer, Heidelberg (2010)Google Scholar
  12. 12.
    Moab Adaptive Computing Suite. http://www.adaptivecomputing.com/products/moab-adaptive-computing-suite.php. Accessed November 2014
  13. 13.
    Kannan, S., Roberts, M., Mayes, P., et al.: Workload Management with LoadLeveler. IBM, New York (2001)Google Scholar
  14. 14.
    Tsafrir, D., Etsion, Y., Feitelson, D.: Backfilling using system-generated predictions rather than user runtime estimates. J. IEEE Trans. on Parallel Distrib. Sys. 18(6), 789–803 (2007)CrossRefGoogle Scholar
  15. 15.
    Toporkov, V., Toporkova, A., Tselishchev, A., Yemelyanov, D., Potekhin, P.: Preference-based fair resource sharing and scheduling optimization in grid vos. J. Procedia Comput. Sci. 29, 831–843 (2014)CrossRefGoogle Scholar
  16. 16.
    Toporkov, V., Toporkova, A., Tselishchev, A., Yemelyanov, D., Potekhin, P.: Core heuristics for preference-based scheduling in virtual organizations of utility grids. In: Camacho, D., Braubach, L., Venticinque, S., Badica, C. (eds.) IDCVIII. SCI, vol. 570, pp. 309–318. Springer, Heidelberg (2014)Google Scholar
  17. 17.
    Toporkov, V., Toporkova, A., Tselishchev, A., Yemelyanov, D.: Slot selection algorithms in distributed computing. J. of Supercomputing 69(1), 53–60 (2014)CrossRefGoogle Scholar
  18. 18.
    Zhou, Z., Lan, Z., Tang, W., Desai, N.: Reducing energy costs for ibm blue gene/p via power-aware job scheduling. In: 17th Workshop on Job Scheduling Strategies for Parallel Processing, pp. 96–115. Boston (2013)Google Scholar
  19. 19.
    Soner, S., Özturan, C.: Integer programming based heterogeneous cpu-gpu cluster scheduler for slurm resource manager. In: 14th IEEE International Conference on High Performance Computing and Communication and 9th IEEE International Conference on Embedded Software and Systems, pp. 418–424. IEEE, Liverpool (2012)Google Scholar
  20. 20.
    Toporkov, V., Tselishchev, A., Yemelyanov, D., Potekhin, P.: Metascheduling strategies in distributed computing with non-dedicated resources. In: Zamojski, W., Sugier, J. (eds.) DPCIS. AISC, vol. 307, pp. 129–148. Springer, Heidelberg (2014)Google Scholar
  21. 21.
    Vanderster, D.C., Dimopoulos, N.J., Parra-hernandez, R., Sobie, R.J.: Resource allocation on computational grids using a utility model and the knapsack problem. J. Future Gener. Comput. Syst. 25(1), 35–50 (2009)CrossRefGoogle Scholar
  22. 22.
    Toporkov, V., Tselishchev, A., Yemelyanov, D., Bobchenkov, A.: Composite scheduling strategies in distributed computing with non-dedicated resources. J. Procedia Comput. Sci. 9, 176–185 (2012)CrossRefGoogle Scholar
  23. 23.
    Rodero, I., Villegas, D., Bobroff, N., Liu, Y., Fong, L., Sadjadi, S.M.: Enabling interoperability among grid meta-schedulers. J. Grid Comput. 11(2), 311–336 (2013)CrossRefGoogle Scholar
  24. 24.
    Aida, K., Casanova, H.: Scheduling mixed-parallel applications with advance reservations. In: 17th IEEE Int. Symposium on HPDC, pp. 65–74. IEEE CS Press, New York (2008)Google Scholar
  25. 25.
    Ando, S., Aida, K.: Evaluation of scheduling algorithms for advance reservations. In: Information Processing Society of Japan SIG Notes HPC-113, pp. 37–42 (2007)Google Scholar
  26. 26.
    Elmroth, E., Tordsson, J.: A standards-based grid resource brokering service supporting advance reservations, coallocation and cross-grid interoperability. J. of Concurrency Comput. 25(18), 2298–2335 (2009)CrossRefGoogle Scholar
  27. 27.
    Azzedin, F., Maheswaran, M., Arnason, N.: A synchronous co-allocation mechanism for grid computing systems. Cluster Comput. 7, 39–49 (2004)CrossRefGoogle Scholar
  28. 28.
    Castillo, C., Rouskas, G.N., Harfoush, K.: Resource co-allocation for large-scale distributed environments. In: 18th ACM International Symposium on High Performance Distributed Compuing, pp. 137–150. ACM, New York (2009)Google Scholar
  29. 29.
    Takefusa, A., Nakada, H., Kudoh, T., Tanaka, Y.: An advance reservation-based co-allocation algorithm for distributed computers and network bandwidth on QoS-guaranteed grids. In: Frachtenberg, E., Schwiegelshohn, U. (eds.) JSSPP 2010. LNCS, vol. 6253, pp. 16–34. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  30. 30.
    Blanco, H., Guirado, F., Lérida, J.L., Albornoz, V.M.: MIP model scheduling for multi-clusters. In: Caragiannis, I., et al. (eds.) Euro-Par Workshops 2012. LNCS, vol. 7640, pp. 196–206. Springer, Heidelberg (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Victor Toporkov
    • 1
    Email author
  • Anna Toporkova
    • 2
  • Alexey Tselishchev
    • 3
  • Dmitry Yemelyanov
    • 1
  • Petr Potekhin
    • 1
  1. 1.National Research University “MPEI”MoscowRussia
  2. 2.National Research University Higher School of EconomicsMoscowRussia
  3. 3.European Organization for Nuclear Research (CERN)Geneva, 23Switzerland

Personalised recommendations