E-Commerce Lab, CSA, IISc1
A Combinatorial Procurement Auction for QOS-Aware Web
Services CompositionMegha Mohabey, Y. Narahari
Computer Science and Automation,Indian Institute of Science, Bangalore
Sudeep Mallik, P. Suresh, S.V. SubrahmanyaInfosys Technologies
Bangalore
September 2007
E-Commerce Lab, CSA, IISc2
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, IISc3
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, IISc4
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, IISc5
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, IISc6
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, IISc7
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, IISc8
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, IISc9
QoS Monitoring
Abstract Process Designer
QoS RegistryQoS Ranking
Enhanced UDDI
Discovery Engine
Preprocessor
OptimizationProblem
Formulator
IP Solver
OptimalSolution
Web Service Binder and
Execution Engine
WSP 1 WSP n
Web Service Web Service
QWESC (QoS-Aware WEb Services Composer)
Publish (WSDL)
Web Service Requestor
Serv
ice
Tem
pla
te
Matching Service
Advertisements
Query
Response
Service Description
Message Exchange (SOAP)
QoS
Feed
back
PaymentDetermination
QoS Feedback
E-Commerce Lab, CSA, IISc10
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, IISc11
Notation
E-Commerce Lab, CSA, IISc12
IP Formulation
E-Commerce Lab, CSA, IISc13
Experimental Results
Announcements by WSPs
E-Commerce Lab, CSA, IISc14
Experimental Results (contd…)
E-Commerce Lab, CSA, IISc15
Experimental Results (contd…)
THE VALUE OF VARIOUS ATTRIBUTES(C - WITH COMBINATORIAL BIDS, NC - WITHOUT COMBINATORIAL BIDS)
E-Commerce Lab, CSA, IISc16
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, IISc17
Questions and Answers …
Thank You …
