El-Bastawissy, AliNagy, WalaaM. O. Mokhtar, Hoda2019-10-192019-10-192011[1] J. Rao and X. Su, “A survey of automated Web service composition methods,” in Proceedings of the irst International orkshop on Semantic Web Services and Web Process Composition, San Diego, California, USA, 2004, pp. 43–54. [2] A. Averbakh, D. Krause, and D. Skoutas, “Exploiting user feedback to improve semantic Web service discovery,” in IS C 2009: Proceedings of the 8th International Semantic Web Conference. Springer-Verlag, 2009, pp. 33–48. [3] R. Krummenacher, M. Hepp, A. Polleres, C. Bussler, and D. Fensel, “ ww or what is wrong with Web services discovery,” in Proceedings of the Third European Conference on Web Services, ser. ECO S ’05. Washington, DC, USA: IEEE Computer Society, 2005. [4] D. Martin, M. Burstein, G. Denker, J. Hobbs, L. Kagal, O. Lassila, D. McDermott, S. McIlraith, M. Paolucci, B. Parsia, T. Payne, M. Sabou, E. Sirin, M. Solanki, . Srinivasan, and K. Sycara, “Bringing semantics to Web services: The OWL-S approach,” in irst International orkshop on Semantic Web Services and Web Process Composition (SWSWPC 2004), San Diego, CA, 2004, pp. 243–277. [5] A. B.Bener, O. Volkan, and I. E. Savas, “Semantic matchmaker with precondition and effect matching using S RL,” Expert Syst. Appl., vol. 36, no. 5, pp. 9371–9377, 2009. [6] L. Cabral, J. Domingue, E. Motta, T. Payne, and F. Hakimpour, “Approaches to semantic Web services: An overview and comparisons,” The Semantic Web Research and Applications, vol. 3053, pp. 225–239, 2004. [7] “Owl-s: Semantic markup for Web services,” 20 . [8] K. Pyar, “Decision support system for personnel information using data warehouse,” in The 2nd Int. Conference on Computer and Automation Engineering (ICCAE). IEEE, 2010, pp. 668–672. [9] L. Zhaoa, Y. Renc, M. Lib, and K. Sakuraia, “ lexible service selection with user-specific QoS support in service-oriented architecture,” network and computer application, 2011. [10] H. Q. Yu and S. Reiff-Marganiec, “ on-functional property based service selection: A survey and classification of approaches,” NonFunctional Properties and Service Level Agreements in Service Oriented Computing Workshop colocated with The 6th IEEE European Conference on Web Services, vol. 411, pp. 13–25, 2008. [11] D. A. Menasc, E. Casalicchio, and V. Dubey, “On optimal service selection in service oriented architectures,” Performance Evaluation, vol. 67, no. 8, pp. 659–675, 2010. [12] S. Agarwal and R. Studer, “Automatic matchmaking of Web services,” in Proceedings of the IEEE International Conference on Web Services. IEEE Computer Society, 2006, pp. 45–54. [13] H. Q. Yu and S. Reiff-Marganiec, “A backwards composition context based service selection approach for service composition,” 2009 IEEE International Conference on Services Computing, pp. 419–426, 2009. [14] C. Platzer and S. Dustdar, “A vector space search engine for Web services,” in Proceedings of the Third European Conference on Web Services, ser. ECO S ’05. ashington, DC, USA: IEEE Computer Society, 2005, pp. 62–71. [15] X. Dong, A. Halevy, J. Madhavan, E. emes, and J. Zhang, “Similarity search for Web services,” in Proceedings of the Thirtieth international conference on Very large data bases, ser. VLDB ’04. VLDB Endowment, 2004, pp. 372–383. [16] S. Ran, “A model for Web services discovery with QoS,” SIGecom Exch., vol. 4, pp. 1–10, March 2003. [17] L. Zeng, B. Benatallah, M. Dumas, J. Kalagnanam, and Q. Z. Sheng,“Quality driven Web services composition,” in Proceedings of the 12th international conference on World Wide Web, ser. ’03. ew York, NY, USA: ACM, 2003, pp. 411–421. [18] D. A. Menasc´e, “QoS issues in Web services,” IEEE Internet Computing, vol. 6, pp. 72–75, November 2002. [19] D. Liu, Z. Shao, C. Yu, and G. an, “A heuristic qos-aware service selection approach to Web service composition,” 2009 Eighth IEEEACIS International Conference on Computer and Information Science, pp.1184–1189, 2009. [20] “UDDI version 3.0.2 specifications,” http : uddi:xml:org , 20 . [21] M. Tian, A. Gramm, T. aumowicz, H. Ritter, and J. Schiller, “A concept for QoS integration in Web services,” in Proceedings of the Fourth international conference on Web information systems engineering workshops, ser. ISE ’03. ashington, DC, USA: IEEE Computer Society, 2003, pp. 149–155. [22] A. Sheth, J. Cardoso, J. Miller, and K. Kochut, “QoS for service-oriented middleware,” in Proceedings of the Sixth orld Multi-Conference on Systemics, Cybernetics and Informatics (SCI02), 2002, pp. 528–534. [23] Y. Liu, A. H. gu, and L. Z. Zeng, “QoS computation and policing in dynamic Web service selection,” in Proceedings of the 3th international World Wide Web conference on Alternate track papers & posters, ser. Alt. ’04. ew York, Y, USA: ACM, 2004, pp. 66–73. [24] . Ibrahim, . L. Mou¨el, and S. r´enot, “Mysim: a spontaneous service integration middleware for pervasive environments,” in Proceedings of the 2009 international conference on Pervasive services, ser. ICPS ’09. ew York, Y, USA: ACM, 2009, pp. –10. [25] E. Al-Masri and Q. H. Mahmoud, “Discovering the best Web service,” in Proceedings of the 16th international conference on World Wide Web, ser. ’07. ew York, Y, USA: ACM, 2007, pp. 1257–1258. [26] T. Yu, Y. Zhang, and K.-J. Lin, “Efficient algorithms for Web services selection with end-to-end QoS constraints,” ACM Trans. Web, vol. 1, May 2007. [27] 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, pp. 311–327, May 2004. [28] D. A. Menasce, “Qos issues in Web services,” IEEE Internet Computing, vol. 6, no. 6, pp. 72–75, 2002. [29] S. hye Jang, V. Taylor, X. Wu, and M. Prajugo, “Performance predictionbased versus load-based site selection: quantifying the difference,” in Proceedings of the 8th international conference on parallel and distributed computing systems, Las Vegas, Nevada, 2005. [30] M. Klusch, B. ries, and K. Sycara, “O LS-MX: A hybrid semantic Web service matchmaker for OWL-S services,” Web Semantics: Science, Services and Agents on the World Wide Web, vol. 7, no. 2, pp. 121 –133, 2009. [31] . Ahmadi and . Binder, “ lexible matching and ranking of Web service advertisements,” in Proceedings of the 2nd workshop on Middleware for service oriented computing: held at the ACM/IFIP/USENIX International Middleware Conference, ser. M 4SOC ’07. ew York, Y, USA: ACM, 2007, pp. 30–35. [32] W. H. Inmon, Building the Data Warehouse, 3rd Edition. New York, NY, USA: John Wiley & Sons, Inc., 2002. [33] “GT information services monitoring &discovery system MDS ,” http://www.globus.org/toolkit/mds/, 2011.https://cutt.ly/3rYp2IPMSA Google ScholarWeb Services are emerging technologies that enable application to application communication and reuse of services over Web. Semantic Web improves the quality of existing tasks, including Web services discovery, invocation, composition, monitoring, and recovery through describing Web services capabilities and content in a computer interpretable language. To provide most of the requested Web services, a Web service matchmaker is usually required. Web service matchmaking is the process of finding an appropriate provider for a requester through a middle agent. To provide the right service for the right user request, Quality of service (QoS)-based Web service selection is widely used. Employing QoS in Web service selection helps to satisfy user requirements through discovering the best service(s) in terms of the required QoS. Inspired by the mode of the Internet Web search engine, like Yahoo, Google, in this paper we provide a QoS-based service selection algorithm that is able to identify the best candidate semantic Web service(s) given the description of the requested service(s) and QoS criteria of user requirements. In addition, our proposed approach proposes a ranking method for those services. We also show how we employ data warehousing techniques to model the service selection problem. The proposed algorithm integrates traditional match making mechanism with data warehousing techniques. This integration of methodologies enables us to employ the historical preference of the user to provide better selection in future searches. The main result of the paper is a generic framework that is implemented to demonstrate the feasibility of the proposed algorithm for QoS-based Web application. Our presented experimental results show that the algorithm indeed performs well and increases the system reliability.enOctober University for University for Semantic WebWeb servicesData warehousesQuality of ServicesArticlehttps://doi.org/10.14569/IJACSA.2011.021229