A Comparative Analysis Between EGEE and GridWay Workload Management Systems

  • J. L. Vázquez-Poletti
  • E. Huedo
  • R. S. Montero
  • I. M. Llorente
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4276)


Metascheduling is a key functionality of the grid middleware in order to achieve a reasonable degree of performance and reliability, given the changing conditions of the computing environment. In this contribution a comparative analysis between two major grid scheduling philosophies is shown: a semi-centralized approach, represented by the EGEE Workload Management System, and a fully distributed approach, represented by the GridWay Metascheduler. This comparative is both theoretical, through a functionality checklist, and experimental, through the execution of a fusion plasma application on the EGEE infrastructure.


Grid Resource Grid Infrastructure Resource Broker Grid Schedule Global Grid Forum 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Yu, J., Buyya, R.: A Taxonomy of Workflow Management Systems for Grid Computing. Journal of Grid Computing 3, 171–200 (2005)CrossRefGoogle Scholar
  2. 2.
    Buyya, R., Abramson, D., Giddy, J.: Nimrod/G: An Architecture for a Resource Management and Scheduling System in a Global Computational Grid. In: Fourth International Conference on High-Performance Computing in the Asia-Pacific Region, vol. 1, p. 283 (2000)Google Scholar
  3. 3.
    Frey, J., Tannenbaum, T., Livny, M., Foster, I., Tuecke, S.: Condor-G: A Computation Management Agent for Multi-Institutional Grids. In: HPDC 2001: Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing (HPDC-10 2001), p. 55. IEEE Computer Society, Los Alamitos (2001)CrossRefGoogle Scholar
  4. 4.
    Dail, H., Sievert, O., Berman, F., Casanova, H., YarKhan, A., Vadhiyar, S., Dongarra, J., Liu, C., Yang, L., Angulo, D., Foster, I.: Scheduling in the Grid Application Development Software Project. In: Grid resource management: state of the art and future trends, pp. 73–98. Kluwer Academic Publishers, Dordrecht (2004)Google Scholar
  5. 5.
    Berman, F., Wolski, R., Casanova, H., Cirne, W., Dail, H., Faerman, M., Figueira, S., Hayes, J., Obertelli, G., Schopf, J., Shao, G., Smallen, S., Spring, N., Su, A., Zagorodnov, D.: Adaptive Computing on the Grid Using AppLeS. IEEE Transactions on Parallel and Distributed Systems 14, 369–382 (2003)CrossRefGoogle Scholar
  6. 6.
    Huedo, E., Montero, R.S., Llorente, I.M.: A Framework for Adaptive Execution on Grids. Intl. J. Software – Practice and Experience (SPE) 34, 631–651 (2004)CrossRefGoogle Scholar
  7. 7.
    Vázquez-Poletti, J., Montero, R.S., Llorente, I.M.: Coordinated Harnessing of the IRISGrid and EGEE Testbeds with GridWay. Journal of Parallel and Distributed Computing 66, 763–771 (2006)CrossRefGoogle Scholar
  8. 8.
    Llorente, I.M., Montero, R.S., Huedo, E.: A Loosely Coupled Vision for Computational Grids. IEEE Distributed Systems Online 6 (2005)Google Scholar
  9. 9.
    Campana, S., Litmaath, M., Sciaba, A.: LCG-2 Middleware Overview (2004), available at: https://edms.cern.ch/document/498079/0.1
  10. 10.
    Huedo, E., Montero, R.S., Llorente, I.M.: Coordinated use of globus pre-WS and WS resource management services with gridway. In: Meersman, R., Tari, Z., Herrero, P. (eds.) OTM-WS 2005. LNCS, vol. 3762, pp. 234–243. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  11. 11.
    Avellino, G., Beco, S., Cantalupo, B., et al.: The DataGrid Workload Management System: Challenges and Results. Journal of Grid Computing 2, 353–367 (2004)CrossRefGoogle Scholar
  12. 12.
    Morajko, A., Fernández, E., Fernández, A., Heymann, E., Senar, M.Á.: Workflow management in the crossGrid project. In: Sloot, P.M.A., Hoekstra, A.G., Priol, T., Reinefeld, A., Bubak, M. (eds.) EGC 2005. LNCS, vol. 3470, pp. 424–433. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  13. 13.
    Huedo, E., Montero, R.S., Llorente, I.M.: Evaluating the Reliability of Computational Grids from the End User’s Point of View. Journal of Systems Architecture (in press, 2006)Google Scholar
  14. 14.
    Herrera, J., Montero, R., Huedo, E., Llorente, I.: DRMAA Implementation within the GridWay Framework. In: Workshop on Grid Application Programming Interfaces, 12th Global Grid Forum (GGF12) (2004)Google Scholar
  15. 15.
    Castejon, F., Tereshcenko, M.A., et al.: Electron Bernstein Wave Heating Calculations for TJ-II Plasmas. American Nuclear Society 46, 327–334 (2004)Google Scholar
  16. 16.
    Huedo, E., Montero, R.S., Llorente, I.M.: An evaluation methodology for computational grids. In: Yang, L.T., Rana, O.F., Di Martino, B., Dongarra, J. (eds.) HPCC 2005. LNCS, vol. 3726, pp. 499–504. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  17. 17.
    Montero, R.S., Huedo, E., Llorente, I.M.: Benchmarking of High Throughput Computing Applications on Grids. Parallel Computing (in press, 2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • J. L. Vázquez-Poletti
    • 1
  • E. Huedo
    • 1
  • R. S. Montero
    • 1
  • I. M. Llorente
    • 1
  1. 1.Departamento de Arquitectura de Computadores y Automática, Facultad de InformáticaUniversidad Complutense de MadridMadridSpain

Personalised recommendations