Determining QoS of WS-BPEL Compositions

  • Debdoot Mukherjee
  • Pankaj Jalote
  • Mangala Gowri Nanda
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5364)


With a large number of web services offering the same functionality, the Quality of Service (QoS) rendered by a web service becomes a key differentiator. WS-BPEL has emerged as the de facto industry standard for composing web services. Thus, determining the QoS of a composite web service expressed in BPEL can be extremely beneficial. While there has been much work on QoS computation of structured workflows, there exists no tool to ascertain QoS for BPEL processes, which are semantically richer than conventional workflows. We propose a model for estimating three key QoS parameters - Response Time, Cost and Reliability - of an executable BPEL process from the QoS information of its partner services and certain control flow parameters. We have built a tool to compute QoS of a WS-BPEL process that accounts for most workflow patterns that may be expressed by standard WS-BPEL. Another feature of our QoS approach and the tool is that it allows a designer to explore the impact on QoS of using different software fault tolerance techniques like Recovery blocks, N-version programming etc., thereby provisioning QoS computation of mission critical applications that may employ these techniques to achieve high reliability and/or performance.


Quality of Service composite web services workflows BPEL 


  1. 1.
    OASIS WS-BPEL Technical Committee, Web Services Business Process Execution Language Version 2.0 (2007)Google Scholar
  2. 2.
    Wohed, P., van der Aalst, W.M.P., Dumas, M., ter Hofstede, A.H.M.: Analysis of Web Services Composition Languages: The Case of BPEL4WS. In: Proceedings of the 22nd International Conference on Conceptual Modeling, ER (2003)Google Scholar
  3. 3.
    Jorge, A., Cardoso, S.: Quality of Service and Semantic Composition of Workflows, Ph.D. Thesis, University of Georgia, Athens, Georgia (2002)Google Scholar
  4. 4.
    Zeng, L., Benatallah, B., Ngu, A.H.H., Dumas, M., Kalagnanam, J., Chang, H.: QoS-Aware Middleware for Web Services Composition. IEEE Transactions in Software Engineering (2004)Google Scholar
  5. 5.
    Avizienis, A., Chen, L.: On the implementation of N-version programming for software fault tolerance during execution. In: Proceedings of IEEE COMPSAC (1977)Google Scholar
  6. 6.
    Randell, B.: System structure for software fault tolerance. In: Proceedings of the international conference on Reliable software (1975)Google Scholar
  7. 7.
    Dobson, G.: Using WS-BPEL to Implement Software Fault Tolerance for Web Services. In: Proceedings of the 32nd EUROMICRO Conference on Software Engineering and Advanced Applications, pp. 126–133 (2006)Google Scholar
  8. 8.
    Gorbenko, A., Kharchenko, V., Popov, P., Romanovsky, A., Boyarchuk, A.: Development of Dependable Web Services out of Undependable Web Components, School of Computing Science, University of Newcastle (2004)Google Scholar
  9. 9.
    Looker, N.M., Xu, M.J.: Increasing Web Service Dependability Through Consensus Voting. In: Computer Software and Applications Conference (2005)Google Scholar
  10. 10.
    Mukherjee, D.: QoS in WS-BPEL Processes, M.Tech. Thesis, Department of Computer Science & Engineering, Indian Institute of Technology, Delhi (2008)Google Scholar
  11. 11.
    Grant Ireson, W., Coombs Jr., C.F., Moss, R.Y.: Handbook of Reliability Engineering and Management. McGraw Hill, New York (1996)Google Scholar
  12. 12.
    Hoyland, A., Rausand, M.: System Reliability Theory: Models and Statistical Methods. John Wiley and Sons, Chichester (1994)zbMATHGoogle Scholar
  13. 13.
    Hwang, S.-Y., Wang, H., Tang, J., Srivastava, J.: A probabilistic approach to modeling and estimating the QoS of web-services-based workflows. Journal of Information Sciences (2007)Google Scholar
  14. 14.
    Canfora, G., Penta, M.D., Esposito, R., Villani, M.L.: An approach for QoS-aware service composition based on genetic algorithms. In: Proceedings of the 2005 conference on Genetic and evolutionary computation (2005)Google Scholar
  15. 15.
    Jaeger, M.C., Rojec-Goldmann, G., Muhl, G.: QoS Aggregation for Web Service Composition using Workflow Patterns. In: Proceedings of the Enterprise Distributed Object Computing Conference (2004)Google Scholar
  16. 16.
    Van der Aalst, W.M.P., ter Hofstede, A.H.M., Kiepuszewski, B., Barros, A.P.: Workflow Patterns. Journal of Distributed Parallel Databases (2003)Google Scholar
  17. 17.
    D’Ambrogio, A., Bocciarelli, P.: A model-driven approach to describe and predict the performance of composite services. In: Proceedings of the 6th international workshop on Software and performance (2007)Google Scholar
  18. 18.
    Amsden, J., Gardner, T., Griffin, C., Iyengar, S.: Draft UML 1.4 profile for automated business processes with a mapping to BPEL 1.0 (2004)Google Scholar
  19. 19.
    Reiter, T.: Transformation of Web Service Specification Languages into UML Activity Diagrams, Diploma thesis, University of South Australia (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Debdoot Mukherjee
    • 1
  • Pankaj Jalote
    • 2
  • Mangala Gowri Nanda
    • 1
  1. 1.IBM India Research LabNew Delhi
  2. 2.Indian Institute of TechnologyDelhi

Personalised recommendations