Advertisement

Client-Oriented Preferences Model for QoS Aggregation in Service-Based Applications

  • Nabil Fakhfakh
  • Frédéric Pourraz
  • Hervé Verjus
  • Patrice Moreaux
Part of the Communications in Computer and Information Science book series (CCIS, volume 314)

Abstract

Client satisfaction is considered today as one of the main concern to be ensured by enterprises, especially in e-business, where client position is central. With the spread of concurrency and the increase of functionally equivalent services, QoS became an important criterion, which is closely related to client satisfaction. In this context, we propose an approach to determine the satisfaction degree corresponding to the QoS of service-based applications, with regard to client’s QoS expectations. Our approach is based on a preferences model, which is built only on the basis of client provided information. This preferences model is also based on the 2-additive Choquet operator that supports preferential dependencies. We present a study that compares the results obtained from our preferences model with those of related work, and shows that our approach provides more accurate results in the way that it represents more precisely client satisfaction.

Keywords

Preferences model QoS aggregation Service orchestration Satisfaction degree measurement The Choquet integral 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    van der Aalst, W., ter Hofstede, A., Kiepuszewski, B., Barros, A.: Workflow patterns. Distributed and Parallel Databases 14(1), 5–51 (2003)CrossRefGoogle Scholar
  2. 2.
    Jaeger, C.: Optimising Quality-of-Service for the Composition of Electronic Services. Ph.D. thesis, Berlin University, Germany (2007)Google Scholar
  3. 3.
    Canfora, G., Di Penta, M., Esposito, R., Villani, M.L.: A framework for qos-aware binding and re-binding of composite web services. J. Syst. Softw. 81, 1754–1769 (2008)CrossRefGoogle Scholar
  4. 4.
    Cardoso, J., Miller, J., Sheth, A., Arnold, J.: Modeling quality of service for workflows and web service processes. Journal of Web Semantics 1, 281–308 (2002)CrossRefGoogle Scholar
  5. 5.
    Cliville, V., Berrah, L., Mauris, G.: Quantitative expression and aggregation of performance measurements based on the macbeth multi-criteria method. International Journal of Production Economics 105(1), 171–189 (2007)CrossRefGoogle Scholar
  6. 6.
    Coppolino, L., Romano, L., Mazzocca, N., Salvi, S.: Web services workflow reliability estimation through reliability patterns. In: Security and Privacy in Communications Networks and the Workshops (2007)Google Scholar
  7. 7.
    Bana e Costa, Corte, J., Vansnick, J.: On the mathematical foundation of MACBETH. In: Multiple Criteria Decision Analysis: State of the Art Surveys, International Series in Operations Research & Management Science, vol. 78, pp. 409–437. Springer, New York (2005)Google Scholar
  8. 8.
    Fakhfakh, N., Pourraz, F., Verjus, H.: Quality of service aggregation in e-business applications. In: Proceedings of ICE-B 2011 International Conference on e-Business, pp. 100–110. SciTePress, Sevilla (2011)Google Scholar
  9. 9.
    He, Q., Yan, J., Jin, H., Yang, Y.: Adaptation of Web Service Composition Based on Workflow Patterns. In: Bouguettaya, A., Krueger, I., Margaria, T. (eds.) ICSOC 2008. LNCS, vol. 5364, pp. 22–37. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  10. 10.
    Herssens, C., Jureta, I.J., Faulkner, S.: Capturing and Using QoS Relationships to Improve Service Selection. In: Bellahsène, Z., Léonard, M. (eds.) CAiSE 2008. LNCS, vol. 5074, pp. 312–327. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  11. 11.
    ISO/TC 176: Quality management systems – requirements (November 2008)Google Scholar
  12. 12.
    Mayag, B., Grabisch, M., Labreuche, C.: A characterization of the 2-additive choquet integral through cardinal information. In: Fuzzy Sets and Systems (2010) (in press, corrected proof )Google Scholar
  13. 13.
    Parasuraman, A., Zeithaml, V.A., Berry, L.L.: Alternative scales for measuring service quality: A comparative assessment based on psychometric and diagnostic criteria. Journal of Retailing 70(3), 201–230 (1994)CrossRefGoogle Scholar
  14. 14.
    Qi, M., Huang, X.: The design and analysis of three-dimensional e-business model. In: Proceedings of the 7th International Conference on Electronic Commerce, ICEC 2005, pp. 136–138. ACM, New York (2005)Google Scholar
  15. 15.
    Rosenberg, F.: QoS-Aware Composition of Adaptive Service-Oriented Systems. Ph.D. thesis, Technical University Vienna, Austria (June 2009)Google Scholar
  16. 16.
    Russell, N., Arthur, van der Aalst, W.M.P., Mulyar, N.: Workflow control-flow patterns: A revised view. Tech. rep., BPMcenter.org (2006)Google Scholar
  17. 17.
    Szydlo, T., Zielinski, K.: Method of Adaptive Quality Control in Service Oriented Architectures. In: Bubak, M., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2008, Part I. LNCS, vol. 5101, pp. 307–316. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  18. 18.
    Taher, L., Basha, R., El Khatib, H.: Qos information & computation (qos-ic) framework for qos-based discovery of web services. UPGRADE 6(4) (August 2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Nabil Fakhfakh
    • 1
  • Frédéric Pourraz
    • 1
  • Hervé Verjus
    • 1
  • Patrice Moreaux
    • 1
  1. 1.LISTICUniversity of SavoieAnnecy Le VieuxFrance

Personalised recommendations