Bicriteria Service Scheduling with Dynamic Instantiation for Workflow Execution on Grids

  • Luiz F. Bittencourt
  • Carlos R. Senna
  • Edmundo R. M. Madeira
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5529)


Nowadays the grid is turning into a service-oriented environment. In this context, there exist solutions to the execution of workflows and most of them are web-service based. Additionally, services are considered to exist on a fixed host, limiting the resource alternatives when scheduling the workflow tasks. In this paper we address the problem of dynamic instantiation of grid services to schedule workflow applications. We propose an algorithm to select the best resources available to execute each task of the workflow on the already instantiated services or on services dynamically instantiated when necessary. The algorithm relies on the existence of a grid infrastructure which could provide dynamic service instantiation. Simulation results show that the scheduling algorithm associated with the dynamic service instantiation can bring more efficient workflow execution on the grid.


Execution Time Directed Acyclic Graph Critical Path Grid Service Good Resource 
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.
    Forum, G.G.: Open grid service architecture, version 1.0 (2002),
  2. 2.
    Huhns, M.N., Singh, M.P.: Service-oriented computing: Key concepts and principles. IEEE Internet Computing 9(1), 75–81 (2005)CrossRefGoogle Scholar
  3. 3.
    Dasgupta, G.B., Viswanathan, B.: Inform: integrated flow orchestration and meta-scheduling for managed grid systems. In: Middleware 2007: Proceedings of the 8th ACM/IFIP/USENIX international conference on Middleware, Newport Beach, California, USA, pp. 1–20 (2007)Google Scholar
  4. 4.
    Byun, E.K., Kim, J.S.: Dynagrid: A dynamic service deployment and resource migration framework for WSRF-compliant applications. Parallel Computing 33(4-5), 328–338 (2007)CrossRefGoogle Scholar
  5. 5.
    Qi, L., Jin, H., Foster, I., Gawor, J.: Provisioning for dynamic instantiation of community services. IEEE Internet Computing 12(2), 29–36 (2008)CrossRefGoogle Scholar
  6. 6.
    Topcuoglu, H., Hariri, S., Wu, M.Y.: Performance-effective and low-complexity task scheduling for heterogeneous computing. IEEE Trans. Parallel and Distributed Systems 13(3), 260–274 (2002)CrossRefGoogle Scholar
  7. 7.
    Bittencourt, L.F., Madeira, E.R.M.: A performance oriented adaptive scheduler for dependent tasks on grids. Concurrency and Computation: Practice and Experience 20(9), 1029–1049 (2008)CrossRefGoogle Scholar
  8. 8.
    Senna, C.R., Madeira, E.R.M.: A middleware for instrument and service orchestration in computational grids. In: Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGRID 2007), Rio de Janeiro, Brazil. IEEE Computer Society Press, Los Alamitos (2007)Google Scholar
  9. 9.
    El-Rewini, H., Ali, H.H., Lewis, T.G.: Task scheduling in multiprocessing systems. IEEE Computer 28(12), 27–37 (1995)CrossRefGoogle Scholar
  10. 10.
    Wieczorek, M., Podlipnig, S., Prodan, R., Fahringer, T.: Bi-criteria scheduling of scientific workflows for the grid. In: 8th IEEE International Symposium on Cluster Computing and the Grid (CCGrid 2008), Lyon, France, pp. 9–16. IEEE Computer Society, Los Alamitos (2008)CrossRefGoogle Scholar
  11. 11.
    Yu, J., Buyya, R.: A taxonomy of scientific workflow systems for grid computing. SIGMOD Records 34(3), 44–49 (2005)CrossRefGoogle Scholar
  12. 12.
    Simion, B., Leordeanu, C., Pop, F., Cristea, V.: A hybrid algorithm for scheduling workflow applications in grid environments (ICPDP). In: Meersman, R., Tari, Z. (eds.) OTM 2007, Part II. LNCS, vol. 4804, pp. 1331–1348. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  13. 13.
    Canon, L.C., Jeannot, E.: Scheduling strategies for the bicriteria optimization of the robustness and makespan. In: 11th International Workshop on Nature Inspired Distributed Computing (NIDISC 2008), Miami, Florida, USA (April 2008)Google Scholar
  14. 14.
    Yang, T., Gerasoulis, A.: Dsc: Scheduling parallel tasks on an unbounded number of processors. IEEE Trans. Parallel and Distributed Systems 5(9), 951–967 (1994)CrossRefGoogle Scholar
  15. 15.
    Dogan, A., Özgüner, F.: Biobjective scheduling algorithms for execution time-reliability trade-off in heterogeneous computing systems. Computer Journal 48(3), 300–314 (2005)CrossRefGoogle Scholar
  16. 16.
    Qi, L., Jin, H., Foster, I.T., Gawor, J.: Hand: Highly available dynamic deployment infrastructure for globus toolkit 4. In: 15th Euromicro IPDP, Naples, Italy, pp. 155–162. IEEE Computer Society, Los Alamitos (2007)Google Scholar
  17. 17.
    Zeng, L., Benatallah, B., Ngu, A.H.H., Dumas, M., Kalagnanam, J., Chang, H.: Qos-aware middleware for web services composition. IEEE Transactions on Software Engineering 30(5), 311–327 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Luiz F. Bittencourt
    • 1
  • Carlos R. Senna
    • 1
  • Edmundo R. M. Madeira
    • 1
  1. 1.Institute of ComputingUniversity of Campinas - UNICAMPBrazil

Personalised recommendations