Skip to main content
Log in

Immune algorithm for selecting optimum services in Web services composition

  • Web Services and Workflow Models
  • Published:
Wuhan University Journal of Natural Sciences

Abstract

For the problem of dynamic optimization in Web services composition, this paper presents a novel approach for selecting optimum Web services, which is based on the longest path method of weighted multistage graph. We propose and implement an Immune Algorithm for global optimization to construct composed Web services. Results of the experimentation illustrates that the algorithm in this paper has a powerful capability and can greatly improve the efficiency and veracity in service selection.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Aprinar I B, Aleman-Meza B, Zhang R,et al. Ontology-Driven Web Services Composition Platform.IEEE International Conference on E-Commerce Technology (CEC'04), San Diego, California, 2004.

  2. Zeng L, Benatallah B, Dumas M,et al. Quality Driven Web Services Composition.Proc 12th Int'l Conf World Wide Web (WWW). New York: ACM Press, 2003.

    Google Scholar 

  3. Yu T, Lin K. Service Selection Algorithms for Web Services with End-to-End QoS Constraints.IEEE International Conference on E-Commerce Technology (CEC'04), San Diego, California, 2001, 129–136.

  4. Zeng L, Benatallah B, Ngu A H H,et al. QoS-Aware Middleware for Web Services Composition.IEEE Transactions on Software Engineering, 2004,30(5): 311–327.

    Article  Google Scholar 

  5. Zhang L, Li B, Chao T,et al. Requirements Driven Dynamic Business Process Composition for Web Services Solutions.Journal of Grid Computing, 2004,2(2): 121–140.

    Article  Google Scholar 

  6. King R L, Russ S H, Lambert A B,et al. Artificial Immune System Model for Intelligent Agents.MSU/NSF Engineering Research Cent for Computational Field Simulation Source: Future Generation Computer Systems. San Diego: Elsevier Science, 2001. 335–343.

    Google Scholar 

  7. Jiao L, Du H. Development and Prospect of the Artificial Immune System.Acta Electronica Sinica, 2003,31(10): 1540–1549 (Ch).

    Google Scholar 

  8. Meshref H, Van Landingham H. Artificial Immune Systems: Application to Autonomous Agents, Systems, Man, and Cybernetics.2000 IEEE International Conference, 2000,1: 61–66.

    Google Scholar 

  9. Gao Jian. Study of QoS Routing Algorithms Based on Immune Mechanism and Genetic Algorithms.Microelectronics & Computer, 2003,8: 20–21 (Ch).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhang Bin.

Additional information

Foundation item: Supported by the National Key Technologies Research and Development Program in the 10th Five-Year Plan of China (2004BA721A05)

Biography: GAO Yan (1970-), male, Lecturer, Ph. D. candidate, research direction: Web services, semantic Web.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Yan, G., Jun, N., Bin, Z. et al. Immune algorithm for selecting optimum services in Web services composition. Wuhan Univ. J. Nat. Sci. 11, 221–225 (2006). https://doi.org/10.1007/BF02831735

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02831735

Key words

CLC number

Navigation