ABSTRACT
Due to the changing nature of service-oriented environments, the ability to locate services of interest in such open, dynamic, and distributed environments has become an essential requirement. Current service-oriented architecture standards mainly rely on functional properties, however, service registries lack mechanisms for managing services' non-functional properties. Such non-functional properties are expressed in terms of quality of service (QoS) attributes. QoS for web services allows consumers to have confidence in the use of services by aiming to experience good service performance in terms of waiting time, reliability, and availability. This paper investigates the service selection process, and proposes two approaches; one that is based on a genetic algorithm, and the other is based on a memetic algorithm to match consumers with services based on QoS attributes as closely as possible. Both approaches are compared with an optimal assignment algorithm called the Munkres algorithm, as well as a Random approach. Measurements are performed to quantify the overall match score, the execution time, and the scalability of all approaches.
- Huhns, M.N., Singh, M.P. 2005. Service-Oriented Computing: Key Concepts and Principles. IEEE Internet Computing 9(1): 75--81. Google ScholarDigital Library
- Taher, L., El Khatib, H. 2005. A framework and QoS matchmaking algorithm for dynamic web services selection, Proceedings of the 2nd International Conference on Innovations in Information Technology (IIT'05).Google Scholar
- Balke, W.T., Wagner, M. 2003. Towards personalized selection of web services, In Proceedings of the Int. World Wide Web Conf. (WWW).Google Scholar
- Badr, Y., Abraham, A., Biennier, F., Grosan, C. 2008. Enhancing Web Service Selection by User Preferences of Non-functional Features, Proceedings of the 2008 4th international Conference on Next Generation Web Services Practices. Google ScholarDigital Library
- Lamparter, S., Ankolekar, A., Studer, R., Grimm, S. 2007. Preference-based selection of highly configurable web services, Proceedings of the 16th international conference on World Wide Web (WWW). Google ScholarDigital Library
- Yu, H.Q., Reiff-Marganiec, S. 2008. A Method for Automated Web Service Selection, Proceedings of the 2008 IEEE Congress on Services. Google ScholarDigital Library
- Maximilien, E.M., Singh, M.P. 2004. Toward autonomic web services trust and selection. In Proceedings of the 2nd international Conference on Service Oriented Computing (ICSOC). Google ScholarDigital Library
- D'Mello, D.A., Ananthanarayana, V.S. 2010. Dynamic selection mechanism for quality of service aware web services, Journal of Enterprise Information Systems, Taylor & Francis, vo. 4, no. 1, pp. 1751--7575. Google ScholarDigital Library
- Huang, A.F., Lan, C., Yang, S.J. 2009. An optimal QoS-based Web service selection scheme. Journal of Inf. Sci. vol. 179, no. 19, pp. 3309--3322. Google ScholarDigital Library
- Yu, T., Zhang, Y., Lin, K. 2007. Efficient algorithms for Web services selection with end-to-end QoS constraints, ACM Transaction Web, vol. 1, no. 1, pp. 1--26. Google ScholarDigital Library
- Wang, R., Chi, C., Deng, J. 2009. A Fast Heuristic Algorithm for the Composite Web Service Selection, Proceedings of the Joint international Conferences on Advances in Data and Web Management. Google ScholarDigital Library
- Jaeger, M.C., Mühl, G. 2007. QoS-based selection of services: The implementation of a genetic algorithm, Proceeding of KiVS (Kommunikation in Verteilten Systemen) in Workshop: Service-Oriented Architectures und Service Oriented Computing.Google Scholar
- Ma, Y., Zhang, C. 2008. Quick convergence of genetic algorithm for QoS-driven web service selection, Journal of Computer Networks, vol. 52, no. 5, pp. 1093--1104. Google ScholarDigital Library
- Kuhn, H.W. 1955. The Hungarian method for the assignment problem, Naval Research Logistics, 52(1).Google Scholar
- Kuhn, H.W. 1955. The hungarian method for solving the assignment problem, Naval Research Logistics Quarterly, 2:83.Google ScholarCross Ref
- Munkres, J. 1957. Algorithms for the Assignment and Transportation Problems, Journal of the Society for Industrial and Applied Mathematics, 5:32.Google Scholar
- Bourgeois, F., Lassalle, J.C., 1971. An extension of the munkres algorithm for the assignment problem to rectangular matrices, Commun. ACM, 14(12). Google ScholarDigital Library
- Wikipedia, Hungarian Algorithm, last retrieved March 2011, http://en.wikipedia.org/wiki/Hungarian_algorithm.Google Scholar
- Nedas, K. 2009. Munkres' (Hungarian) Algorithm, Java implementation, last retrieved on March 2009 from http://konstantinosnedas.com/dev/soft/munkres.htm.Google Scholar
- Holland, J.H. 1975. Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor.Google Scholar
- Wolpert, D., Macready, W. 1997. No free lunch theorems for optimization, IEEE Trans. Evol. Comput., vol. 1, no. 1, pp. 67--82. Google ScholarDigital Library
- Dawkins, R. 1976. The Selfish Gene, New York: Oxford Univ. Press.Google Scholar
- Krasnogor, N., Smith, J. 2005. A Tutorial for Competent Memetic Algorithms: Model, Taxonomy, and Design Issues, IEEE Trans. On Evolutionary Computation, vol. 9, no. 5. Google ScholarDigital Library
- Vazquez, M., Whitley, L. 2000. A hybrid genetic algorithm for the quadratic assignment problem, Proc. Genetic Evol. Comput. Conf., D, pp. 135--142.Google Scholar
- Ku, K.,Mak, M. 1998. Empirical analysis of the factors that affect the Baldwin effect, Lecture Notes in Computer Science, Parallel Problem Solving From Nature, pp. 481--490. Google ScholarDigital Library
- Morris, G.M., Goodsell, D.S., Halliday, R.S., Huey, R., Hart, W.E., Belew, R.K., Olson, A.J. 1998. Automated docking using a lamarkian genetic algorithm and an empirical binding free energy function, Journal Comput. Chem., vol. 14, pp. 1639--1662.Google ScholarCross Ref
Index Terms
- Memetic algorithm for web service selection
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