Abstract
For workflow-based service composition approach, the relations between the Web service QoS and environments are usually not considered, so that the information about QoS for composite service selection is inaccurate. It makes the selected composite service inefficient, or even unexecutable. To address this problem, a novel service composition approach based on production QoS rules is proposed in this paper. Generally, it is very difficult to directly analyze how different kinds of environment factors influence the Web service QoS. We adopt “black-box” analysis method of optimizing composite services, discovering the knowledge such as “the QoS of one Web service will be higher in specific environments”. In our approach, the execution information of the composite service is recorded into a log first, which will be taken as the basis of the subsequent statistical analysis and data mining. Then, the timely QoS values of the Web services are estimated and the production QoS rules being used to qualitatively express the different performances of the Web service QoS in different environments are mined. At last, we employ the mined QoS knowledge of the Web services to optimize the composite service selection. Extensive experimental results show that our approach can improve the performance of selected composite services on the premise of assuring the selecting computation cost.
Similar content being viewed by others
References
Milanovic N, Malek M. Current solutions for Web service composition. IEEE Internet Computing, 2004, 8(6): 51–59.
Yu J, Han Y B, Han J et al. Synthesizing service composition models on the basis of temporal business rules. Journal of Computer Science and Technology, 2008, 23(6): 885–894.
Serhani M A, Dssouli R, Hafid A et al. A QoS broker based architecture for efficient Web services selection. In Proc. the IEEE Int. Conf. Web Services, Orlando, USA, July 11–15, 2005, pp.113–120.
Rosenberg F, Platzer C, Dustdar S. Bootstrapping performance and dependability attributes of Web services. In Proc. the IEEE International Conference on Web Services, Chicago, USA, Sept. 18–22, 2006, pp.205–212.
Wang Y, Vassileva J. A review on trust and reputation for Web service selection. In Proc. the 27th Int. Conf. Distributed Computing Systems Workshops, Toronto, Canada, June 22–29, 2007, pp.25–32.
Li H H, Du X Y, Tian X. A review-based reputation evaluation approach for Web services. Journal of Computer Science and Technology, 2009, 24(5): 893–900.
Blum A L, Furst M L. Fast planning through planning graph analysis. Artificial Intelligence, 1997, 90(1/2): 281–300.
Kautz H, Selman B. Unifying sat-based and graph-based planning. In Proc. the 16th Int. Joint Conf. Artificial Intelligence, San Francisco, USA, Aug. 1–6, 1999, pp.318–325.
Oh S C, Lee D W, Kumara S R T. Effective Web service composition in diverse and large-scale service networks. IEEE Transactions on Services Computing, 2008, 1(1): 15–32.
Medjahed B, Bouguettaya A, Elmagarmid A. Composing Web services on the semantic Web. The VLDB Journal, 2003, 12(4): 333–351.
Sirin E, Parsia B, Wu D et al. HTN planning for Web service composition using SHOP2. Journal of Web Semantics, 2004, 1(4): 377–396.
Zeng L, Benatallah B, Kalagnama M et al. Quality driven Web services composition. In Proc. the 12th Int. Conf. World Wide Web, Budapest, Hungary, May 20–24, 2003, pp.411–421.
Ghandeharizadeh S, Knoblock C, Papadopoulos C et al. Proteus: A system for dynamically composing and intelligently executing Web services. In Proc. the 1st IEEE Int. Conf. Web Services, Las Vegas, USA, June 23–26, 2003, pp.17–21.
Altintas I, Jaeger E, Lin K et al. A Web service composition and deployment framework for scientific workflows. In Proc. the 2nd IEEE Int. Conf. Web Services, San Diego, USA, July 6–9, 2004, pp.814–815.
Sun H, Wang X, Zhou B et al. Research and Implementation of Dynamic Web Services Composition. Advanced Parallel Processing Technologies, 2003, LNCS, Vol.2834, pp.457–466.
Zeng L Z, Benatallah B. QoS-aware middleware for Web services composition. IEEE Transactions on Software Engineering, 2004, 30(5): 311–327.
Ardagna D, Pernici B. Global and local QoS guarantee in Web service selection. In BPM 2005 Int. Workshops, Nancy, France, Sept. 5, 2005, LNCS, Vol.3812, pp.32–46.
Yu T, Lin K J. Service selection algorithms for composing complex services with multiple QoS constraints. In Proc. the 3rd Int. Conf. Service Oriented Computing, Amsterdam, Netherlands, Dec. 12–15, 2005, pp.130–143.
Korkmaz T, Krunz M. Multi-constrained optimal path selection. In Proc. the 20th Joint Conf. IEEE Computer and Communications Societies, Anchorage, USA, April 22–26, 2001, pp.834–843.
Canfora G, Penta M D, Esposito R et al. An approach for QoS-aware service composition based on genetic algorithms. In Proc. the Int. Conf. Genetic and Evolutionary Computation, Washington DC, USA, June 25–29, 2005, pp.1069–1075.
Cardellini V, Casalicchio E, Grassi V et al. Flow-based service selection for Web service composition supporting multiple QoS classes. In Proc. the Int. Conf. Web Services, Salt Lake City, USA, July 9–13, 2007, pp.743–750.
Dustdar S, Gombotz R. Discovering Web service workflows using Web services interaction mining. International Journal of Business Process Integration and Management, 2006, 1(4): 256–266.
Cruz S M S, Campos M L M, Pires P F et al. Monitoring e-business Web services usage through a log based architecture. In Proc. the IEEE Int. Conf. Web Services, San Diego, USA, July 6–9, 2004, pp.61–69.
Ringelstein C, Staab S. DIALOG: Distributed auditing logs. In Proc. the IEEE Int. Conf. Web Services, Los Angeles, USA, July 6–10, 2009, pp.429–436
Agrawal R, Imielinski T, Swami A. Mining association rules between sets of items in large databases. In Proc. the ACM Conf. Management of Data, Washington DC, USA, May 25–28, 1993, pp.207–216.
Author information
Authors and Affiliations
Corresponding author
Additional information
This work is supported by the National Natural Science Foundation of China under Grant Nos. 60773218, 60903009 and 61073062, and the National High Technology Research and Development 863 Program of China under Grant No. 2009AA01Z122.
Rights and permissions
About this article
Cite this article
Zhang, MW., Zhang, B., Liu, Y. et al. Web Service Composition Based on QoS Rules. J. Comput. Sci. Technol. 25, 1143–1156 (2010). https://doi.org/10.1007/s11390-010-9395-0
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11390-010-9395-0