Evolutionary Intelligence

, Volume 3, Issue 3–4, pp 171–186 | Cite as

Composition of web services through genetic programming

  • Pablo Rodríguez-Mier
  • Manuel Mucientes
  • Manuel Lama
  • Miguel I. Couto
Research Paper

Abstract

Web Services are interfaces that describe a collection of operations that are network-accessible through standardized web protocols. When a required operation is not found, several services can be compounded to get a composite service that performs the desired task. To find this composite service a search process in a, generally, huge search space must be performed. The algorithm that composes the services must select the adequate atomic processes and, also, must choose the correct way to combine them using the different available control structures. In this paper a genetic programming algorithm for web services composition is presented. The algorithm has a context-free grammar to generate the valid structures of the composite services and, also, it includes a method to update the attributes of each node. Moreover, the proposal tries to minimize the number of services, and looks for compositions with the minimum execution path. A full experimental validation with four different repositories with up to 1,090 web services has been done, showing a great performance in all the tests as the algorithm finds a valid solution with a short execution path.

Keywords

Web services composition Genetic programming Evolutionary algorithms 

Notes

Acknowledgments

This work was supported by the Spanish Ministry of Science and Innovation under Grant TSI2007-65677-C02-02. Manuel Mucientes is supported by the Ramón y Cajal program of the Spanish Ministry of Science and Innovation.

References

  1. 1.
    Aiello M, van Benthem N, Khoury E (2008) Visualizing compositions of services from large repositories. In: Proceedings of the fifth IEEE conference on enterprise computing, e-commerce and e-services (EEE’08). IEEE Computer Society, Washington, DC, pp 359–362.Google Scholar
  2. 2.
    Alamri A, Eid M, Saddik AE (2006) Classification of the state of the art dynamic web services composition techniques. Int J Web Grid Serv 2(2):148–166CrossRefGoogle Scholar
  3. 3.
    Alonso G, Casati F, Kuno H, Machiraju V (2003) Web services. Springer, BerlinGoogle Scholar
  4. 4.
    Anderson BB, Hansen JV, Lowry PB (2009) Creating automated plans for semantic web applications through planning as model checking. Expert Syst Appl 36(7):10595–10603CrossRefGoogle Scholar
  5. 5.
    Aversano L, di Penta M, Taneja K (2006) A genetic programming approach to support the design of service compositions. Int J Comput Syst Sci Eng 4:247–254Google Scholar
  6. 6.
    Bansal A, Blake MB, Kona S, Bleul S, Weise T, Jaeger MC (2008) WSC-08: continuing the web services challenge. In: Proceedings of the 5th IEEE international conference on enterprise computing, e-commerce and e-services (EEE’08). IEEE, pp 351–354Google Scholar
  7. 7.
    Bertoli P, Pistore M, Traverso P (2010) Automated composition of web services via planning in asynchronous domains. Artif Intell 174(3–4):316–361CrossRefMathSciNetGoogle Scholar
  8. 8.
    Blum AL, Furst ML (1997) Fast planning through planning graph analysis. Artif Intell 90(1–2):281–300MATHCrossRefGoogle Scholar
  9. 9.
    Chang W-C, Wu C-S, Chang C (2005) Optimizing dynamic web service component composition by using evolutionary algorithms. In: Proceedings of the 2005 IEEE/WIC/ACM international conference on web intelligence (WI’05). IEEE Computer Society, Washington, DC, pp 708–711Google Scholar
  10. 10.
    Curbera F, Goland Y, Klein J, Leymann F, Roller D, Thatte S, Weerawarana S (2002) Business process execution language for web services, version 1.0, November 2002. Standards proposal by BEA Systems, International Business Machines Corporation, and Microsoft CorporationGoogle Scholar
  11. 11.
    Curbera Francisco, Nagy William A., Weerawana Sanjiva (2001) Web Service: Why and How. In: Proceedings of the OOPSLA-2001 workshop on object-oriented services. Tampa, Florida, USAGoogle Scholar
  12. 12.
    Dustdar S, Schreiner W (2005) A survey on web services composition. Int J Web Grid Serv 1(1):1–30CrossRefGoogle Scholar
  13. 13.
    Hoffmann Jörg, BP, Pistore M (2007) Web service composition as planning, revisited: in between background theories and initial state uncertainty. In: Proceedings of the 22nd national conference on artificial intelligence (AAAI’07). AAAI Press, pp 1013–1018Google Scholar
  14. 14.
    Klusch M, Gerber A (2006) Fast composition planning of owl-s services and application. In: Proceedings of the European conference on web services (ECOWS’06). IEEE Computer Society, Washington, DC, pp 181–190Google Scholar
  15. 15.
    Kuster U, Konig-Ries B, Krug A (2008) Opossum—an online portal to collect and share sws descriptions. In: Proceedings of the 2th IEEE international conference on semantic computing (ICSC 2008). IEEE Computer Society, Santa Clara, pp 480–481Google Scholar
  16. 16.
    Madhusudan T, Uttamsingh N (2006) A declarative approach to composing web services in dynamic environments. Decis Support Syst 41(2):325–357CrossRefGoogle Scholar
  17. 17.
    Martin D, Burstein M, Hobbs J, Lassila O, McDermott D, McIlraith S, Narayanan S, Paolucci M, Parsia B, Payne T, Sirin E, Srinivasan N, Sycara K (2004) OWL-S: semantic markup for web services. World Wide Web Consortium (W3C), November 2004. Available at http://www.w3.org/Submission/OWL-S/
  18. 18.
    Nau D, Au T-C, Ilghami O, Kuter U, Murdock W, Wu D, Yaman F (2003) SHOP2: an HTN planning system. J Artif Intell Res 20(4):379–404MATHGoogle Scholar
  19. 19.
    Oh S-C, Lee D, Kumara SRT (2006) A comparative illustration of ai planning-based web services composition. SIGecom Exch 5(5):1–10CrossRefGoogle Scholar
  20. 20.
    Oh S-C, Lee D, Kumara SRT (2008) Effective web service composition in diverse and large-scale service networks. IEEE Trans Serv Comput 1(1):15–32CrossRefGoogle Scholar
  21. 21.
    Pistore M, Marconi A, Bertoli P, Traverso P (2005) Automated composition of web services by planning at the knowledge level. In Proceedings of the 19th international joint conference on artificial intelligence (IJCAI’05). Morgan Kaufmann Publishers Inc, San Francisco, pp 1252–1259Google Scholar
  22. 22.
    Rao J, Küngas P, Matskin M (2006) Composition of semantic web services using linear logic theorem proving. Inform Syst 31(4):340–360CrossRefGoogle Scholar
  23. 23.
    Ren K, Liu X, Chen J, Xiao N, Song J, Zhang W (2008). A QSQL-based efficient planning algorithm for fully-automated service composition in dynamic service environments. In: Proceedings of the 2008 IEEE international conference on services computing (SCC’08). IEEE Computer Society, Washington, DC, pp 301–308Google Scholar
  24. 24.
    Russell SJ, Norvig P (2009) Artificial intelligence: a modern approach. Prentice Hall, Englewood CliffsGoogle Scholar
  25. 25.
    Sirin E, Parsia B, Wu D, Hendler J, Nau D (2004) Htn planning for web service composition using shop2. J Web Semant 1(4):377–396Google Scholar
  26. 26.
    Vanrompay Y, Rigole P, Berbers Y (2008) Genetic algorithm-based optimization of service composition and deployment. In: Proceedings of the 3rd international workshop on services integration in pervasive environments (SIPE’08). ACM, New York, pp 13–18Google Scholar
  27. 27.
    Wu Z, Gomadam K, Ranabahu A, Sheth AP, Miller JA (2007) Automatic composition of semantic web services using process and data mediation. In: Proceedings of the 9th international conference on enterprise information systems (ICEIS’07). Funchal, Portugal, pp 453–461Google Scholar
  28. 28.
    Xiangbing Z (2010) Semantics web service characteristic composition approach based on particle swarm optimization volume 56 of Lecture Notes in Electrical Engineering. Springer, pp 279–287Google Scholar
  29. 29.
    Zheng X, Yan Y (2008) An efficient syntactic web service composition algorithm based on the planning graph model. In: Proceedings of the 2008 IEEE international conference on web services (ICWS’08). IEEE Computer Society, Washington, DC, pp 691–699Google Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Pablo Rodríguez-Mier
    • 1
  • Manuel Mucientes
    • 1
  • Manuel Lama
    • 1
  • Miguel I. Couto
    • 1
  1. 1.Department of Electronics and Computer ScienceUniversity of Santiago de CompostelaGaliciaSpain

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