Variability-Driven Selection of Services for Service Compositions

  • Kai Petersen
  • Johannes Maria Zaha
  • Andreas Metzger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4907)


In order to deliver services that realize their requirements at low cost, in short time, and with high quality, service engineers reuse existing services for building composite services. For each service that is part of such a composite service and which is offered by a service provider, a service level agreement has to be established and the quality of service has to be monitored. Therefore, in order to keep service management controllable, the overall number of services across all service compositions that are maintained by an organization should be as small as possible. However, currently there exists no technique that would support service engineers in selecting such a minimal set of services when building composite services. By drawing on research results from software product line engineering, we define a service selection process (SeVAR) that exploits the similarities in the requirements in order to select the minimal set of services that achieves the best coverage of those requirements.


Service Composition Variation Point Service Selection Software Product Line Composite Service 
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  1. 1.
    Ardagna, D., Pernici, B.: Global and local qoS guarantee in web service selection. In: Bussler, C.J., Haller, A. (eds.) BPM 2005. LNCS, vol. 3812, pp. 32–46. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  2. 2.
    Benatallah, B., Hacid, M.-S., Léger, A., Rey, C., Toumani, F.: On automating web services discovery. The VLDB Journal 14(1), 84–96 (2005)CrossRefGoogle Scholar
  3. 3.
    Bühne, S., Lauenroth, K., Pohl, K.: Modelling requirements variability across product lines. In: Proceedings of the 13th IEEE International Requirements Engineering Conference (RE 2005), pp. 41–52 (2005)Google Scholar
  4. 4.
    Clements, P., Northrop, L.M.: Software Product Lines: Practices and Patterns. Addison-Wesley Professional, Boston (2001)Google Scholar
  5. 5.
    Kontio, J.: Otso: A systematic process for reusable software component selection. Technical report, University of Maryland (1995)Google Scholar
  6. 6.
    Pohl, K., Böckle, G., van der Linden, F.J.: Software Product Line Engineering: Foundations, Principles and Techniques. Springer, Heidelberg (2005)CrossRefzbMATHGoogle Scholar
  7. 7.
    Saaty, T.L.: Multicriteria decision making - the analytic hierarchy process: Planning, priority setting, resource allocation. RWS Publishing, Pittsburgh (1990)Google Scholar
  8. 8.
    Weiss, D.M., Lai, C.T.R.: Software Product Line Engineering - A Family-Based Software Development Process. Addison-Wesley, Reading (1999)Google Scholar
  9. 9.
    Yu, T., Lin, K.-J.: Service selection algorithms for web services with end-to-end QoS constraints. Journal of Information Systems and e-Business Management 3(2), 103–126 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Kai Petersen
    • 1
  • Johannes Maria Zaha
    • 1
  • Andreas Metzger
    • 1
  1. 1.Software Systems EngineeringUniversity of Duisburg-EssenEssenGermany

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