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A hierarchical framework for logical composition of web services

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Abstract

Automatically composing Web services to form processes in the context of service-oriented architectures has attracted significant research. Prevalent approaches for automatically composing Web services predominantly utilize planning techniques to achieve the composition. However, classical planning based approaches face the following challenges: (i) difficulty in modeling the uncertainty of Web service invocations, (ii) inability to optimize the composition using non-functional parameters, and (iii) difficulty in scaling efficiently to large compositions. In order to address these issues, we present a hierarchical framework for logically composing Web services, which we call Haley. In comparison to classical planners, Haley utilizes decision-theoretic planning that is able to model and reason with the uncertainty inherent in Web service invocations and provides an expected cost-based optimization. Haley uses symbolic planning techniques that operate directly on first-order logic based representations of the state space to obtain the compositions. Consequently, it supports automated elicitation of the corresponding planning problem from Web service descriptions and produces a domain representation that is more compact than that of classical planners. Furthermore, it promotes scalability by exploiting the natural hierarchy found in real-world processes. Due to the limitations of the existing approaches and the complexity of the Web service composition problem, few implemented tools exist, although many approaches have been proposed in the literature. We have implemented Haley and provided a comprehensive tool suite for composing Web services. The suite operates on Web services described using well-known languages such as SAWSDL. It provides process designers with an intuitive interface to specify composition requirements, goals and a hierarchical decomposition if available, and automatically generates BPEL compositions while hiding the complexity of the planning and of BPEL from users.

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References

  1. Singh M, Huynhs M (2005) Service-oriented computing: semantics, processes and agents. Wiley, New York

    Google Scholar 

  2. Gudgin M, Hadley M, Mendelsohn N, Moreau JJ, Nielsen HF, Karmarkar A, Lafon Y (2007) Simple object access protocol (soap), version 1.2. http://www.w3.org/tr/soap12-part1

  3. Chinnici R, Moreau JJ, Ryman A, Weerawarana S (2007) Web services description language (wsdl), version 2.0. http://www.w3.org/tr/2007/rec-wsdl20-20070626

  4. Wu D, Parsia B, Sirin E, Hendler JA, Nau DS (2003) Automating DAML-S web services composition using SHOP2. In: International aemantic web conference (ISWC), pp 195–210

  5. Kuter U, Sirin E, Nau D, Parsia B, Hendler J (2005) Information gathering during planning for web serivce composition. J Web Semant 3: 183–205

    Google Scholar 

  6. Rao J, Su X (2004) A survey of automated web service composition methods. In: Workshop on semantic web services and web process composition (SWSWPS), pp 43–54

  7. McIlraith S, Son TC (2002) Adapting Golog for composition of semantic web services. In: International conference on principles and knowledge representation and reasoning (KR-02), Toulouse, France, pp 482–496

  8. Medjahed B, Bouguettaya A, Elmagarmid AK (2003) Composing web services on the semantic web. VLDB J 12(4): 333–351

    Article  Google Scholar 

  9. Traverso P, Pistore M (2004) Automated composition of semantic web services into executable processes. In: International semantic web conference (ISWC), pp 380–394

  10. Pistore M, Marconi A, Bertoli P, Traverso P (2005) Automated composition of web services by planning at the knowledge level. In: International joint conferences on artificial intelligence (IJCAI), pp 1252–1259

  11. Oh SC, Lee D, Kumara SRT (2007) Web service planner (wspr): an effective and scalable web service composition algorithm. Int J Web Serv Res (JWSR) 4: 1–22

    Google Scholar 

  12. Qiu L, Chang L, Lin F, Shi Z (2007) Context optimization of ai planning for semantic web services composition. J Serv Oriented Comput Appl 1(2): 117–128

    Article  Google Scholar 

  13. Bylander T (1991) Complexity results for planning. In: International joint conference of artificial intelligence (IJCAI), pp 274–279

  14. Blythe J (1999) Decision-theoretic planning. AI Mag 20(2): 37–54

    Google Scholar 

  15. Bellman RE (1957) Dynamic programming. Dover, New York

    Google Scholar 

  16. Doshi P, Goodwin R, Akkiraju R, Verma K (2005) Dynamic workflow composition: using markov decision processes. J Web Serv Res (JWSR) 2(1): 1–17

    Google Scholar 

  17. Zhao H, Doshi P (2006) A hierarchical framework for composing nested web processes. In: International conference on service oriented computing (ICSOC), pp 116–128

  18. Martin DL, Burstein MH, McDermott DV, McIlraith SA, Paolucci M, Sycara KP, McGuinness DL, Sirin E, Srinivasan N (2007) Bringing semantics to web services with OWL-S. In: International world wide web conference (WWW), pp 243–277

  19. Farrell J, Lausen H (2006) SAWSDL: semantic annotations for wsdl. http://www.w3.org/tr/sawsdl/

  20. der Aalst WV, Hee KV (2004) Workflow management: models, methods and systems. MIT Press, Cambridge

    Google Scholar 

  21. Puterman M (1994) Markov decision processes: discrete stochastic dynamic programming. Wiley-Interscience, London

    MATH  Google Scholar 

  22. Boutilier C, Reiter R, Price B (2001) Symbolic dynamic programming for first-order MDPs. In: International joint conferences on artificial intelligence (IJCAI), pp 690–700

  23. Holldobler S, Skvortsova O (2004) A logic-based approach to dynamic programming. In: Learning and planning in Markov processes-advances and challenges-AAAI 04 workshop, pp 31–36

  24. Kersting K, Otterlo MV, Raedt LD (2004) Bellman goes relational. In: Twenty-first international conference on machine learning (ICML), pp 465–472

  25. Hirtle D, Boley H, Grosof B, Kifer M, Sintek M, Tabet S, Wagner G (2006) Schema specification of RuleML. http://www.ruleml.org/0.91/

  26. McCarthy J (1963) Situations, actions and causal laws. Technical report, AI Laboratory, Stanford University

  27. Reiter R (2001) Knowledge in action: logical foundations for specifying and implementing dynamic systems. MIT Press, Cambridge

    Google Scholar 

  28. Sanner S, Boutilier C (2005) Approximate linear programming for first-order MDPs. In: Twenty-first conference in uncertainty in artificial intelligence, pp 509–517

  29. Ludwig H, Keller A, Dan A, King R, Franck R (2003) Web service level agreement (wsla) language specification. http://www.research.ibm.com/wsla

  30. 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 (2006) OWL-S: semantic markup for web services. http://www.daml.org/services/owl-s/1.1

  31. Andrieux A, Czajkowski K, Dan A, Keahey K, Ludwig H, Nakata T, Pruyne J, Rofrano J, Tuecke S, Xu M (2007) Web services agreement specification (ws-agreement). http://forge.gridforum.org/sf/projects/graap-wg

  32. Horrocks I, Patel-Schneider PF, Boley H, Tabet S, Grosof B, Dean M (2004) Swrl: a semantic web rule language combining owl and ruleml. http://www.w3.org/submission/swrl

  33. Boutilier C, Reiter R, Soutchanski M, Thrun S (2000) Decision-theoretic, high-level agent programming in the situation calculus. In: Seventeenth conference on artificial intelligence, pp 355–362

  34. Cimatti A, Pistore M, Roveri M, Traverso P (2003) Weak, strong, and strong cyclic planning via symbolic model checking. Artif Intell 147(1–2): 35–84

    MATH  MathSciNet  Google Scholar 

  35. Morell J, Swiecki B (2001) E-readiness of the automotive supply chain: just how wired is the supplier sector. Technical report, Center for Automotive Research, Center for Electronic Commerce, ERIM

  36. Turing A (1936) On computable numbers, with an application to the entscheidungs problem. Proc Lond Math Soc 42: 230–265

    Article  MATH  Google Scholar 

  37. Nau DS, Au TC, Ilghami O, Kuter U, Murdock JW, Wu D, Yaman F (2003) SHOP2: an HTN planning system. J Artif Intell Res (JAIR) 20: 379–404

    MATH  Google Scholar 

  38. Sirin E, Parsia B, Wu D, Hendler JA, Nau DS (2004) HTN planning for web service composition using SHOP2. J Web Semant 1(4): 377–396

    Google Scholar 

  39. McIlraith SA, Son TC, Zeng H (2001) Semantic web services. IEEE Intell Syst 16: 45–53

    Article  Google Scholar 

  40. Benatallah B, Sheng QZ, Dumas M (2003) The Self-Serv environment for web services composition. IEEE Internet Comput 7(1): 40–48

    Article  Google Scholar 

  41. Aggarwal R, Verma K, Miller JA, Milnor W (2004) Constraint driven web service composition in METEOR-S. In: IEEE international conference on services computing (SCC), pp 23–30

  42. Cardoso J, Miller J, Sheth A, Arnold J (2004) Quality of service for workflows and web service processes. J Web Semant 1: 281–308

    Google Scholar 

  43. Zeng L, Benatallah B, Dumas M, Kalagnanam J, Sheng QZ (2003) Quality driven web services composition. In: International world wide web conference (WWW), pp 411–421

  44. Canfora G, Esposito R (2004) A lightweight approach for QoS-aware service composition. In: Second international conference on service oriented computing (ICSOC), pp 36–47

  45. Wiesemann W, Hochreiter R, Kuhn D (2008) A stochastic programming approach for QoS-aware service composition. In: IEEE international symposium on cluster computing and the grid (CCGrid), pp 226–233

  46. Agarwal V, Chafle G, Dasgupta K, Karnik NM, Kumar A, Mittal S, Srivastava B (2005) Synthy: a system for end to end composition of web services. J Web Semant 3(4): 311–339

    Google Scholar 

  47. Chafle G, Das G, Dasgupta K, Kumar A, Mittal S, Mukherjea S, Srivastava B (2007) An integrated development environment for web service composition. In: IEEE international conference on web services (ICWS), pp 839–847

  48. Nagarajan M, Verma K, Sheth AP, Miller JA (2007) Ontology driven data mediation in web services. Int J Web Serv Res (JWSR) 4(4): 104–126

    Google Scholar 

  49. Rohanimanesh K, Mahadevan S (2001) Decision-theoretic planning with concurrent temporally extended actions. In: Uncertainty in artificial intelligence (UAI), pp 472–479

  50. Kiepuszewski B, ter Hofstede AHM, Bussler C (2000) On structured workflow modelling. In: Conference on advanced information systems engineering (CAiSE), pp 431–445

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Correspondence to Prashant Doshi.

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Zhao, H., Doshi, P. A hierarchical framework for logical composition of web services. SOCA 3, 285–306 (2009). https://doi.org/10.1007/s11761-009-0052-9

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  • DOI: https://doi.org/10.1007/s11761-009-0052-9

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