A Novel Genetic Algorithm for QoS-Aware Web Services Selection

  • Chengwen Zhang
  • Sen Su
  • Junliang Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4055)


A novel genetic algorithm characterized by improved fitness value is presented for Quality of Service (QoS)-aware web services selection. The genetic algorithm includes a special relation matrix coding scheme of chromosomes, an initial population policy and a mutation policy. The relation matrix coding scheme suits with QoS-aware web service composition more than the one dimension coding scheme. By running only once, the proposed genetic algorithm can construct the composite service plan according with the QoS requirement from many services compositions. Meanwhile, the adoption of the initial population policy and the mutation policy promotes the fitness of genetic algorithm. Experiments on QoS-aware web services selection show that the genetic algorithm with this matrix can get more excellent composite service plan than the genetic algorithm with the one dimension coding scheme, and that the two policies play an important role at the improvement of the fitness of genetic algorithm.


Genetic Algorithm Service Composition Composite Service Concrete Service Mutation Policy 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    W3C. Web Services Architecture (2004),
  2. 2.
    Menascé, D.A.: QoS Issues in Web Services. IEEE Internet Computing 6(6), 72–75 (2002)CrossRefGoogle Scholar
  3. 3.
    Menascé, D.A.: Composing Web Services: A QoS View. IEEE Internet Computing, 88–90 (2004)Google Scholar
  4. 4.
    Tian, M., Gramm, A., Ritter, H., Schiller, J.: Efficient Selection and Monitoring of QoS-Aware Web Services with the WS-QoS Framework. In: IEEE/WIC/ACM International Conference on Web Intelligence (WI 2004) (2004)Google Scholar
  5. 5.
    Bilgin, A.S., Singh, M.P.: A DAML-Based Repository for QoS-Aware Semantic Web Service Selection. In: Proceedings of the IEEE International Conference on Web Services (ICWS 2004) (2004)Google Scholar
  6. 6.
    Zhou, C., Chia, L.-T., Lee, B.-S.: DAML-QoS Ontology for Web Services. In: IEEE International Conference on Web Services (ICWS 2004) (2004)Google Scholar
  7. 7.
    Liu, Y., Ngu, A.H., Zeng, L.: QoS Computation and Policing in Dynamic Web Service Selection. In: Proceedings of the 13th International Conference on World Wide Web (WWW), pp. 66–73. ACM Press, New York (2004)Google Scholar
  8. 8.
    Zeng, L., Benatallah, B., Dumas, M., Kalagnanam, J., Sheng, Q.Z.: Quality Driven Web Services Composition. In: Proc. 12th Int’l. Conf. World Wide Web (WWW) (2003)Google Scholar
  9. 9.
    Zeng, L., Benatallah, B., Ngu, A.H.H., et al.: QoS-Aware Middleware for Web Services Composition. IEEE Transactions on Software Engineering 30(5), 311–327 (2004)CrossRefGoogle Scholar
  10. 10.
    Zhang, L., Li, B., Chao, T., et al.: On Demand Web Services-Based Business Process Composition. IEEE, 4057–4064 (2003)Google Scholar
  11. 11.
    Canfora, G., Di Penta, M., Esposito, R., Villani, M.L.: A Lightweight Approach for QoS–Aware Service Composition. In: ICSOC (2004)Google Scholar
  12. 12.
    Ignacio, R., Jesús, G., Héctor, P., et al.: Statistical Analysis of the Main Parameters Involved in the Design of a Genetic Algorithm. IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews 32(1), 31–37 (2002)CrossRefGoogle Scholar
  13. 13.
    Srinivas, M., Patnaik, L.M.: Genetic Algorithm: a Survey. IEEE, 17–26 (1994)Google Scholar
  14. 14.
    Hinterding, R., Michalewicz, Z., Eiben, A.E.: Adaptation in Evolutionary Computation: a Survey. IEEE EC, 65–69 (1997)Google Scholar
  15. 15.
    Curbera, F., Khalaf, R., Mukhi, N., et al.: The Next Step in Web Services. Communication of the ACM 46(10), 29–34 (2003)CrossRefGoogle Scholar
  16. 16.
    Milanovic, N., Malek, M.: Current Solutions for Web Service Composition. IEEE Internet Computing, 51–59 (2004)Google Scholar
  17. 17.
    Orriens, B., Yang, J., Papazoglou, M.P.: Model Driven Service Composition. In: Orlowska, M.E., Weerawarana, S., Papazoglou, M.P., Yang, J. (eds.) ICSOC 2003. LNCS, vol. 2910, pp. 75–90. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  18. 18.
    ISO 8402, Quality VocabularyGoogle Scholar
  19. 19.
    ITU-T Recommendation E.800, Terms and Definitions Related to Quality of Service and Network Performance Including Dependability (1994) Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chengwen Zhang
    • 1
  • Sen Su
    • 1
  • Junliang Chen
    • 1
  1. 1.State Key Lab of Networking and Switching TechnologyBeijing University of Posts & Telecommunications (BUPT)BeijingChina

Personalised recommendations