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Optimization Techniques for QoS-Aware Workflow Realization in Web Services Context

  • Joyce El Haddad
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6799)

Abstract

With the evolution of Web services technologies, a lot has been done to answer users needs throughout service composition. Service selection is an important step of the service composition process. Multiple services functionally equivalent might be offered by different providers but characterized by different Quality of Service (QoS) values. Since the QoS of the selected services has an impact on the QoS of the produced composite service, the best set of services to be selected is the set that maximize the QoS of the composite service. In the literature, many approaches have been proposed for the QoS-aware service selection problem which has been formalized as an optimization problem. This paper is devoted to the presentation of some optimization techniques and their application to the service selection problem.

Keywords

Service Composition Service Selection Composite Service Candidate Service Concrete Service 
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.

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References

  1. 1.
    Zeng, L., Benatallah, B., Ngu, A.H.H., Dumas, M., Kalagnanam, J., Chang, H.: Qos-aware middleware for web services composition. IEEE Trans. on Software Eng. 30(5), 311–327 (2004)CrossRefGoogle Scholar
  2. 2.
    Bonatti, P.A., Festa, P.: On optimal service selection. In: Proceedings of the 14th international conference on World Wide Web, pp. 530–538. ACM, New York (2005)CrossRefGoogle Scholar
  3. 3.
    Yu, T., Lin, K.J.: Service selection algorithms for web services with end-to-end qos constraints. Information Systems and E-Business Management 3(2), 103–126 (2005)CrossRefGoogle Scholar
  4. 4.
    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
  5. 5.
    Cardellini, V., Casalicchio, E., Grassi, V., Lo Presti, F.: Flow-based service selection for web service composition supporting multiple qos classes. In: IEEE International Conference on Web Services, pp. 743–750. IEEE Computer Society, Los Alamitos (2007)CrossRefGoogle Scholar
  6. 6.
    Wan, C., Ullrich, C., Chen, L., Huang, R., Luo, J., Shi, Z.: On solving qos-aware service selection problem with service composition. In: Seventh International Conference on Grid and Cooperative Computing, pp. 467–474. IEEE Computer Society, Los Alamitos (2008)CrossRefGoogle Scholar
  7. 7.
    Canfora, G., Di Penta, M., Esposito, R., Villani, M.: An approach for qos-aware service composition based on genetic algorithms. In: GECCO 2005: Proceedings of the 2005 Conference on Genetic and Evolutionary Computation, pp. 1069–1075. ACM, New York (2005)Google Scholar
  8. 8.
    Ko, J.M., Kim, C.O., Kwon, I.H.: Quality-of-service oriented web service composition algorithm and planning architecture. J. Syst. Softw. 81(11), 2079–2090 (2008)CrossRefGoogle Scholar
  9. 9.
    Zhang, W., Chang, C.K., Feng, T., Jiang, H.: Qos-based dynamic web service composition with ant colony optimization. In: IEEE 34th Annual Computer Software and Applications Conference, pp. 493–502 (2010)Google Scholar
  10. 10.
    Alrifai, M., Risse, T.: Combining global optimization with local selection for efficient qos-aware service composition. In: Proceedings of the 18th International Conference on World Wide Web, pp. 881–890. ACM, New York (2009)CrossRefGoogle Scholar
  11. 11.
    Ben Mabrouk, N., Beauche, S., Kuznetsova, E., Georgantas, N., Issarny, V.: Qos-Aware Service Composition in Dynamic Service Oriented Environments. In: Bacon, J.M., Cooper, B.F. (eds.) Middleware 2009. LNCS, vol. 5896, pp. 123–142. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  12. 12.
    Izquierdo, D., Vidal, M.-E., Bonet, B.: An expressive and efficient solution to the service selection problem. In: Patel-Schneider, P.F., Pan, Y., Hitzler, P., Mika, P., Zhang, L., Pan, J.Z., Horrocks, I., Glimm, B. (eds.) ISWC 2010, Part I. LNCS, vol. 6496, pp. 386–401. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  13. 13.
    Puchinger, J., Raidl, G.R.: Combining metaheuristics and exact algorithms in combinatorial optimization: A survey and classification. In: Mira, J., Álvarez, J.R. (eds.) IWINAC 2005. LNCS, vol. 3562, pp. 41–53. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  14. 14.
    Chinneck, J.: Practical Optimization: a Gentle Introduction. online textbook (2000),http://www.sce.carleton.ca/faculty/chinneck/po.html
  15. 15.
    Blum, C., Roli, A.: Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Comput. Surv. 35(3), 268–308 (2003)CrossRefGoogle Scholar
  16. 16.
    Zhang, C., Su, S., Chen, J.: A novel genetic algorithm for qos-aware web services selection. Data Engineering Issues in E-Commerce and Services, 224–235 (2006)Google Scholar
  17. 17.
    Jaeger, M., Mühl, G.: Qos-based selection of services: The implementation of a genetic algorithm. In: KiVS Workshop, Service-Oriented Architectures and Service Oriented Computing, pp. 359–370 (2007)Google Scholar
  18. 18.
    Cao, L., Li, M., Cao, J.: Using genetic algorithm to implement cost-driven web service selection. Multiagent Grid Syst 3(1), 9–17 (2007)CrossRefzbMATHGoogle Scholar
  19. 19.
    Vanrompay, Y., Rigole, P., Berbers, Y.: Genetic algorithm-based optimization of service composition and deployment. In: Proceedings of the 3rd International Workshop on Services Integration in Pervasive Environments, SIPE 2008, pp. 13–18. ACM, New York (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Joyce El Haddad
    • 1
  1. 1.Université Paris-Dauphine, LAMSADE - CNRS UMR 7243Paris Cedex 16France

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