Applied Intelligence

, Volume 36, Issue 1, pp 1–28 | Cite as

Dynamic planning approach to automated web service composition

  • Mehmet Kuzu
  • Nihan Kesim Cicekli


In this paper, novel ideas are presented for solving the automated web service composition problem. Some of the possible real world problems such as partial observability of the environment, nondeterministic effects of web services and service execution failures are solved through a dynamic planning approach. The proposed approach is based on a novel AI planner that is designed for working in highly dynamic environments under time constraints, namely Simplanner. World altering service calls are done according to the WS-Coordination and WS-Business Activity web service transaction specifications in order to physically recover from failure situations and prevent the undesired side effects of the aborted web service composition efforts.


Semantic web services Automated web service composition Automated web service invocation AI planning Simplanner 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Rao J, Su X (2004) A survey of automated web service composition methods. In: Proceedings of 1st international workshop on semantic web services and web process composition, pp 43–54 Google Scholar
  2. 2.
    Milanovic N, Malek M (2004) Current solutions for web service composition. IEEE Trans Internet Comput 8(6):51–59 CrossRefGoogle Scholar
  3. 3.
    Srivastava B, Koehler J (2003) Web service composition—current solutions and open problems. In: Proceedings of ICAPS’03 workshop on planning for web services, Trento, Italy, 2003, pp 28–35 Google Scholar
  4. 4.
    Agarwal V, et al (2008) Understanding approaches for web service composition and execution. In: Proceedings of the 1st Bangalore annual compute conference, India, 2008, pp 1–8 Google Scholar
  5. 5.
    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):148–166 CrossRefGoogle Scholar
  6. 6.
    Polleres A (2004) AI planning for web service composition. Presentation, Ilog, Paris, France, 2004.
  7. 7.
    Sapena O, Onaindia E (2007) Planning in highly dynamic environments: an anytime approach for planning under time constraints. J Appl Intell 29(1):90–109 CrossRefGoogle Scholar
  8. 8.
    OASIS (2006) Web services business activity specification.
  9. 9.
    OWL-S Semantic markup for web services.
  10. 10.
  11. 11.
    Sirin E, Parsia B, Wu D, Hendler J, Nau D (2004) HTN planning for web service composition using SHOP2. J Web Semant 1(4):377–396 CrossRefGoogle Scholar
  12. 12.
    Nau D, Au TC, Ilghami O, Kuter U, Murdock W, Wu D, Yaman F (2003) SHOP2: an HTN planning system. J Artif Intell Res (JAIR) 20:379–404 zbMATHGoogle Scholar
  13. 13.
    OASIS (2006) Web services coordination specification.
  14. 14.
    Klusch M, Gerber A, Schmidt M (2005) Semantic web service composition planning with OWLS-XPlan. In: Proceedings of the AAAI fall symposium on semantic web and agents, Arlington VA, USA. AAAI Press, Menlo Park Google Scholar
  15. 15.
    Hoffmann J (2003) The metric-FF planning system: translating ignoring delete lists to numeric state variables. J Artif Intell Res (JAIR) 20:291–341 zbMATHGoogle Scholar
  16. 16.
    Klusch M, Renner K-U (2006) Fast dynamic re-planning of composite OWL-S services. In: Proceedings of IEEE/WIC/ACM international conferences on web intelligence and intelligent agent technology—workshops, 2006, pp 134–137 Google Scholar
  17. 17.
    Peer J (2004) A PDDL based tool for automatic web service composition. In: Proceedings of the 2nd international workshop on principles and practice of semantic web reasoning, 2004, pp 149–163 Google Scholar
  18. 18.
  19. 19.
    Peer J (2005) Semantic service markup with SESMA. In: Proceedings of the web service semantics workshop (WSS’05) at the 14th international world wide web conference (WWW’05), 2005, Chiba, Japan, pp 100–116 Google Scholar
  20. 20.
    Younes HLS, Simmons RG (2003) VHPOP: versatile heuristic partial order planner. J Artif Intell Res (JAIR) 20:405–430 zbMATHGoogle Scholar
  21. 21.
    Gerevini A, Saetti A, Serina I (2003) Planning through stochastic local search and temporal action graphs. J Artif Intell Res 20(1):239–290 zbMATHGoogle Scholar
  22. 22.
    Agarwal V, Dasgupta K, Karnik N, Kumar A, Kundu A, Mittal S, Srivastava B (2005) A service creation environment based on end to end composition of web services. In: Proceedings of the 14th international conference on world wide web, Chiba, Japan, 2005, pp 128–137 Google Scholar
  23. 23.
  24. 24.
    Bartalos SP, Bieliková M (2008) Enhancing semantic web services composition with user interaction. In: Proceedings of the IEEE international conference on services computing (SCC), Honolulu, Hawaii, USA, 2008, pp 503–506 Google Scholar
  25. 25.
    Marconi SA, Pistore M, Traverso P (2008) Automated composition of web services: the ASTRO approach. IEEE Data Eng Bull 31(3):23–26 Google Scholar
  26. 26.
    Digiampietri LA, Alcázar JJP, Medeiros CB (2008) AI planning in web services composition: a review of current approaches and a new solution. In: Proceedings of the XXVII Brazilian computer society conference (CSBC), July 2008 Google Scholar
  27. 27.
    Wiesner K, Vaculín R, Kollingbaum MJ, Sycara KP (2009) Recovery mechanisms for semantic web services. In: Meier R, Terzis S (eds) International conference on distributed applications and interoperable systems (DAIS). LNCS, vol 5053. Springer, Berlin, pp 100–105 CrossRefGoogle Scholar
  28. 28.
    Kazhamiakin R, Bertoli P, Paolucci M, Pistore M, Wagner M (2009) Having services “YourWay!”: towards user-centric composition of mobile services. In: Future Internet FIS 2008. LNCS, vol 5468. Springer, Berlin, pp 94–106 CrossRefGoogle Scholar
  29. 29.
    Bryce D, Kambhampati S (2007) A tutorial on planning graph-based reachability heuristics. AI Mag 28(1):47–83 Google Scholar
  30. 30.
    Ghallab M, Howe A, Knoblock C, McDermott D, Ram A, Veloso M, Weld D, Wilkins D (1998) PDDL: the planning domain definition language, AIPS-98 planning committee Google Scholar
  31. 31.
    Smith MK, Welty C, McGuinness DL OWL web ontology language guide.
  32. 32.
    Christensen E, Curbera F, Meredith G, Weerawarana S Web services description language (WSDL) 1.1.
  33. 33.
    Kim H, Kim I (2007) Mapping semantic web service descriptions to planning domain knowledge. Proc IFMBE 14(1):388–391 CrossRefGoogle Scholar
  34. 34.
  35. 35.
    WSIF Web services invocation framework.
  36. 36.
    Axis Apache web services project.
  37. 37.
    OASIS (2006) Web services atomic transaction specification.
  38. 38.
    Erven H, Hicker G, Huemer C, Zaptletal M (2007) The web services-business activity-initiator (WS-BA-I) protocol: an extension to the web services-business activity specification. In: IEEE international conference on web services (ICWS), 2007, Salt Lake City, pp 216–224 Google Scholar
  39. 39.
    Kandula Apache WS-transaction project.,
  40. 40.
  41. 41.
    Mindswap Web service composer software.
  42. 42.
    Srivastava B (2004) A software framework for building planners. In: Proceedings of knowledge based computer systems (KBCS), 2004, Hyderabad, pp 382–392 Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of Texas at DallasRichardsonUSA
  2. 2.Department of Computer EngineeringMiddle East Technical UniversityAnkaraTurkey

Personalised recommendations