A Combinatorial Procurement Auction for QOS-Aware Web Services Composition - PowerPoint PPT Presentation

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  1. A Combinatorial Procurement Auction for QOS-Aware Web Services Composition Megha Mohabey, Y. Narahari Computer Science and Automation, Indian Institute of Science, Bangalore Sudeep Mallik, P. Suresh, S.V. Subrahmanya Infosys Technologies Bangalore September 2007 E-Commerce Lab, CSA, IISc

  2. Overview • Web Services Composition Problem • Motivation, Research Gap and Contributions • QWESC: A Tool for QOS-Aware Web Service Composition • Combinatorial Auction for Web Services Composition • Conclusions and Future Work E-Commerce Lab, CSA, IISc

  3. Web Services • Network-resident software services accessible via standardized protocols • Can be automatically exposed, discovered, and invoked by other applications • Business processes and application functionality are becoming available as web services . • Can be endogenous or exogenous • Available often as commercial web services from enterprise solution vendors and web services marketplaces. • Eg.www.strikeiron.com, www.amazon.com, www.google.com E-Commerce Lab, CSA, IISc

  4. Web Services Composition Problem • Types of web services: • Stand-alone Web Services - Represent a single activity in a business process • Composite Web Services - Represent more complex business logic often encompassing multiple business steps • Web Service Providers (WSPs) may offer web services with different Quality of Service (QoS) and service level agreement (SLA) guarantees. • Dynamic creation of business processes requires composing an appropriate set of web services that best suit the current need. E-Commerce Lab, CSA, IISc

  5. Problem Definition • To find the best mix of web services that achieves well defined cost and quality criteria for the execution of an end-to-end composite service as desired by a WSR • We propose an approach to get the optimal execution plan for a single execution path. A B C A Simple Statechart E-Commerce Lab, CSA, IISc

  6. Related Work • L. Zeng, B. Benatallah, A. H. Ngu, M. Dumas, J. Kalagnanam, and H. Chang, “Qos-aware middleware for web services composition,” IEEE Trans. Softw. Eng., vol. 30, no. 5, pp. 311–327, 2004. • QoS modeling and QoS aware web services composition • Y. Gao, B. Zhang, J. Na, L. Yang, Y. Dai, and Q. Gong, “Optimal selection of web services for composition based on interface-matching and weighted multistage graph,” in PDCAT ’05: Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies. Washington, DC, USA: IEEE Computer Society, 2005, pp. 336–338. • Interface matching • G. Canfora, M. D. Penta, R. Esposito, and M. L. Villani, “An approach for qos-aware service composition based on genetic algorithms,” in GECCO ’05: Proceedings of the 2005 conference on Genetic and evolutionary computation. New York, NY, USA: ACM Press, 2005, pp. 1069–1075. • Genetic algorithm based approach E-Commerce Lab, CSA, IISc

  7. Research Gap and Contributions • Current approaches consider the problem of composition of stand-alone web services to form an end-to-end composite service. • We present a novel combinatorial auction approach to dynamic web services composition that considers both stand-alone and composite services for forming an end-to-end composite service. • We design a software tool, QWESC (QoS-Aware WEb Services Composer), for web services composition based on the proposed approach. E-Commerce Lab, CSA, IISc

  8. Motivating Scenarios for Combinatorial Auction Approach • A WSP may be willing to provide a composite service at a price lower than the total price of stand-alone services that form the composite service. • The quality attributes of a composite service offered by a WSP may not be the same as achieved by composing its constituent stand-alone services. • Different WSPs may have different number of stages/steps for achieving the same task and they can expose the services at different points. E-Commerce Lab, CSA, IISc

  9. QWESC (QoS-Aware WEb Services Composer) Enhanced UDDI Publish (WSDL) QoS Registry QoS Ranking Query WSP 1 WSP n Response Service Description QoS Feedback Discovery Engine Web Service Web Service Message Exchange (SOAP) Matching Service Advertisements Service Template Web Service Binder and Execution Engine Preprocessor Abstract Process Designer Optimization Problem Formulator QoS Monitoring Optimal Solution Web Service Requestor IP Solver QoS Feedback Payment Determination E-Commerce Lab, CSA, IISc

  10. Combinatorial Auction Approach • A web service requestor (WSR) wishes to buy a set of distinct web services A . • There is a set of web service providers (WSPs) who are interested in selling the entire set or some subsets of A. • The WSPs submit combinatorial bids • If a WSP can provide services A, B, C, AB, and BC, and there are two quality attributes, then the bid will look as follows: < ({A}, q1, q2, c(A)), ({B}, q1, q2, c(B)), ({C}, q1, q2, c(C)), ({A,B}, q1, q2, c(AB)), ({B,C}, q1, q2, c(BC)) > E-Commerce Lab, CSA, IISc

  11. Notation E-Commerce Lab, CSA, IISc

  12. IP Formulation E-Commerce Lab, CSA, IISc

  13. Experimental Results Announcements by WSPs E-Commerce Lab, CSA, IISc

  14. Experimental Results (contd…) E-Commerce Lab, CSA, IISc


  16. Future Work • Generalized Model • Current work limits discussion to that of a linear execution path. • Introducing forks and joins will model a more generalized scenario. • Interface Matching and SLA handling • The services offered by different WSPs may not be interoperable, if they have incompatible input output interfaces. • WSPs may provide service at various levels of quality guarantee violation of which may attract some form of penalty. • Game Theoretic Approach • A rational WSP may not find it in its best response to reveal true information about the web services provided by it. • To ensure truth revelation by WSPs, an appropriate incentive scheme has to be designed. E-Commerce Lab, CSA, IISc

  17. Questions and Answers … Thank You … E-Commerce Lab, CSA, IISc