Heuristic Approaches for QoS-Based Service Selection

  • Diana Comes
  • Harun Baraki
  • Roland Reichle
  • Michael Zapf
  • Kurt Geihs
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6470)


In a Service Oriented Architecture (SOA) business processes are commonly implemented as orchestrations of web services, using the Web Services Business Process Execution Language (WS-BPEL). Business processes not only have to provide the required functionality, they also need to comply with certain Quality-of-Service (QoS) constraints which are part of a service-level agreement between the service provider and the client. Different service providers may offer services with the same functionality but different QoS properties, and clients can select from a large number of service offerings. However, choosing an optimal collection of services for the composition is known to be an NP-hard problem.

We present two different approaches for the selection of services within orchestrations required to satisfy certain QoS requirements. We developed two algorithms, OPTIM_HWeight and OPTIM_PRO, which perform a heuristic search on the candidate services. The OPTIM_HWeight algorithm is based on weight factors and the OPTIM_PRO algorithm is based on priority factors. We evaluate and compare the two algorithms with each other and also with a genetic algorithm.


Service Selection Heuristic Function Candidate Service Abstract Service Gradient Ascent 
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.


  1. 1.
    Bleul, S., Comes, D., Geihs, K.: Automatic Service Brokering in Service oriented Architectures, Homepage,
  2. 2.
    Canfora, G., Penta, M., 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. ACM, Washington (2005)Google Scholar
  3. 3.
    Zeng, L., Benatallah, B., Ngu, A.H., Dumas, M., Kalagnanam, J., Chang, H.: QoS-Aware Middleware for Web Services Composition. In: IEEE Transactions on Software Engineering, pp. 311–327. IEEE Press, Los Alamitos (2004)Google Scholar
  4. 4.
    Comes, D., Bleul, S., Weise, T., Geihs, K.: A Flexible Approach for Business Processes Monitoring. In: Senivongse, T., Oliveira, R. (eds.) DAIS 2009. LNCS, vol. 5523, pp. 116–128. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  5. 5.
    Jaeger, M., Múhl, G., Golze, S.: QoS-aware Composition of Web Services: An Evaluation of Selection Algorithms. In: International Symposium on Distributed Objects and Applications (DOA 2005). Springer, Heidelberg (2005)Google Scholar
  6. 6.
    Berbner, R., Spahn, M., Repp, N., Heckmann, O., Steinmetz, R.: Heuristics for QoS-aware Web Service Composition. In: IEEE International Conference on Web Services (ICWS 2006). IEEE Computer Society, Los Alamitos (2006)Google Scholar
  7. 7.
    Web Services Business Process Execution Language Version 2.0, OASIS standard (2007),
  8. 8.
  9. 9.
    Baligand, F., Rivierre, N., Ledoux, T.: A Declarative Approach for QoS-Aware Web Service Compositions. In: Krämer, B.J., Lin, K.-J., Narasimhan, P. (eds.) ICSOC 2007. LNCS, vol. 4749, pp. 422–428. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  10. 10.
    Parejo, J., Fernandez, A., Cortes, P., QoS-Aware Services, A.: composition using Tabu Search and Hybrid Genetic Algorithms. Actas de los Talleres de las Jornadas de Ingeniería del Software y Bases de Datos 2(1) (2008)Google Scholar
  11. 11.
    Garey, M., Johnson, D.: Computers and Intractability; A Guide to the Theory of NP-Completeness. W. H. Freeman and Co, New York (1979)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Diana Comes
    • 1
  • Harun Baraki
    • 1
  • Roland Reichle
    • 1
  • Michael Zapf
    • 1
  • Kurt Geihs
    • 1
  1. 1.Distributed Systems GroupUniversity of KasselKasselGermany

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