Advertisement

SCPOPS: An Efficient and Effective Method for Service Discovery and Composition

  • Yuanyuan Jiang
  • Ying Zhang
  • Song Huang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 113)

Abstract

In order to improve the efficiency of service discovery and composition, we first define a property ordered pairs called Property Ordered PairS (POPS) and some function of it in this paper. Then we propose a service discovery and a composition algorithm based on the POPS, the Service composition based on the POPS (SCPOPS) algorithm. We present the SCPOPS algorithm in detail and give an instance. Finally, we take some simulation experiment by the SCPOPS algorithm, the result shows it is efficient and effective for service discovery and composition.

Keywords

SOA POPS Service composition SCPOPS 

References

  1. 1.
    Barker A, Walton CD, Robertson D (2009) Choreographing web services[J]. IEEE Trans Serv Comput 2(2):152–166CrossRefGoogle Scholar
  2. 2.
    Rao J, Su X (2004) A survey of automated web service composition methods[C]. In: Proceedings of first international workshop on semantic web services and web process compositionGoogle Scholar
  3. 3.
    Xiangwei L, Zhicai X, Li Y (2009) Independent global constraints-aware web service composition optimization based on genetic algorithm[C]. In: Proceedings of international conference on industrial and information systemsGoogle Scholar
  4. 4.
    Bellwood T, Capell S, Clement L, Colgrave J, Dovey MJ, Feygin D, Hately A, Kochman R, Macias P, Novotny M, Paolucci M, von Riegen C, Rogers T, Sycara K, Wenzel P, Wu Z (2002) UDDI version 3.0[EB/OL]. http://uddi.org/pubs/uddi_v3.htm
  5. 5.
    Lee SY, Lee JY, Lee BI (2006) Service composition techniques using data mining for ubiquitous computing environments. Int J Comput Sci Netw Secur[J]. 6(9):110–117Google Scholar
  6. 6.
    Xu B, Li T, Gu Z et al (2006) SWSDS: quick web service discovery and composition in SEWSIP. In: Proceedings of the 8th IEEE international conference on ecommerce technology and the 3rd IEEE international conference on enterprise computing, e-commerce, and e-servicesGoogle Scholar
  7. 7.
    Kuang L, Li Y, Wu J et al (2007) Inverted indexing for composition-oriented service discovery[C]. In: Proceedings of IEEE international conference on web services (ICWS)Google Scholar
  8. 8.
    Qiu L, Shi Z, Lin F (2006) Context optimization of AI planning for services composition[C]. In: Proceedings of the IEEE international conference on e-business engineering, pp 610–617Google Scholar
  9. 9.
    Madhusudan T, Uttamsingh N (2006) A declarative approach to composing web services in dynamic environments[J]. Decis Support Syst 41(2):325–357CrossRefGoogle Scholar
  10. 10.
    Bottaro A, Bourcier J, Escoer C et al (2007) Autonomic context-aware service composition[C]. In: Proceedings of 2nd IEEE international conference on pervasive servicesGoogle Scholar
  11. 11.
    Mingkhwan A, Fergus P, Abuelma’Atti O et al (2006) Dynamic service composition in home appliance networks. Multimed Tools Appl[J] 29(3):257–284Google Scholar
  12. 12.
    Pourreza H, Graham P (2006) On the fly service composition for local interaction environments[C]. In: Proceedings of IEEE international conference on pervasive computing and communications workshops, 393Google Scholar
  13. 13.
    Viroli M, Denti E, Ricci A (2007) Engineering a BPEL orchestration engine as a multi-agent system[J]. Sci Comput Program 66:226–245CrossRefMATHMathSciNetGoogle Scholar
  14. 14.
    Chi YL, Lee HM (2008) A formal modeling platform for composing web services[J]. Expert Syst Appl 34:1500–1507CrossRefGoogle Scholar
  15. 15.
    Valero V, Cambronero ME, Díaz G et al (2009) A Petri net approach for the design and analysis of web services choreographies[J]. J Log Algebraic Program 78:359–380CrossRefMATHGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.PLA University of Science and TechnologyNanjingChina

Personalised recommendations