Abstract
The concept of Service-Oriented Architecture, where individual services can be combined to accomplish more complex tasks, provides a flexible and reusable approach to application development. Their composition can be performed manually, however doing so may prove to be challenging if many service alternatives with differing qualities are available. Evolutionary Computation (EC) techniques have been employed successfully to tackle this problem, especially Genetic Programming (GP), since it is capable of encoding conditional constraints on the composition’s execution paths. While compositions can naturally be represented as Directed Acyclic Graphs (DAGs), GP needs to encode candidates as trees, which may pose conversion difficulties. To address that, this work proposes an extension to an existing EC approach that represents solutions directly as DAGs. The tree-based and extended graph-based composition approaches are compared, showing significant gains in execution time when using graphs, sometimes up to two orders of magnitude. The quality levels of the solutions produced, however, are somewhat higher for the tree-based approach. This, in addition to a convergence test, shows that the genetic operators employed by the graph-based approach can be potentially improved. Nevertheless, the extended graph-based approach is shown to be capable of handling compositions with multiple conditional constraints, which is not possible when using the tree-based approach.
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References
Brown, N., McKay, B., Gilardoni, F., Gasteiger, J.: A graph-based genetic algorithm and its application to the multiobjective evolution of median molecules. J. Chem. Inf. Comput. Sci. 44(3), 1079–1087 (2004)
Gottschalk, K., Graham, S., Kreger, H., Snell, J.: Introduction to Web services architecture. IBM Syst. J. 41(2), 170–177 (2002)
Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection, vol. 1. MIT Press, Cambridge (1992)
Ma, H., Schewe, K.D., Wang, Q.: An abstract model for service provision, search and composition. In: Proceedings of the 2009 IEEE Asia-Pacific Services Computing Conference (APSCC), pp. 95–102. IEEE (2009)
Ma, H., Wang, A., Zhang, M.: A hybrid approach using genetic programming and greedy search for QoS-aware Web service composition. In: Hameurlain, A., Küng, J., Wagner, R., Decker, H., Lhotska, L., Link, S. (eds.) Transactions on Large-Scale Data- and Knowledge-Centered Systems XVIII. LNCS, vol. 8980, pp. 180–205. Springer, Heidelberg (2015). doi:10.1007/978-3-662-46485-4_7
Mabu, S., Hirasawa, K., Hu, J.: A graph-based evolutionary algorithm: genetic network programming (GNP) and its extension using reinforcement learning. Evol. Comput. 15(3), 369–398 (2007)
Menasce, D.: QoS issues in Web services. IEEE Internet Comput. 6(6), 72–75 (2002)
Milanovic, N., Malek, M.: Current solutions for Web service composition. IEEE Internet Comput. 8(6), 51–59 (2004)
Nicolaou, C.A., Apostolakis, J., Pattichis, C.S.: De novo drug design using multiobjective evolutionary graphs. J. Chem. Inf. Model. 49(2), 295–307 (2009)
Perrey, R., Lycett, M.: Service-oriented architecture. In: 2003 Proceedings of the Symposium on Applications and the Internet Workshops, pp. 116–119. IEEE (2003)
Rodriguez-Mier, P., Mucientes, M., Lama, M., Couto, M.I.: Composition of Web services through genetic programming. Evol. Intell. 3(3–4), 171–186 (2010)
Silva, A.S., Ma, H., Zhang, M.: GraphEvol: a graph evolution technique for Web service composition. In: Chen, Q., Hameurlain, A., Toumani, F., Wagner, R., Decker, H. (eds.) DEXA 2015. LNCS, vol. 9262, pp. 134–142. Springer, Heidelberg (2015). doi:10.1007/978-3-319-22852-5_12
da Silva, A.S., Ma, H., Zhang, M.: A GP approach to QoS-aware Web service composition including conditional constraints. In: 2015 IEEE Congress on Evolutionary Computation (CEC), pp. 2113–2120. IEEE (2015)
Sohrabi, S., Prokoshyna, N., McIlraith, S.A.: Web service composition via the customization of golog programs with user preferences. In: Borgida, A.T., Chaudhri, V.K., Giorgini, P., Yu, E.S. (eds.) Conceptual Modeling: Foundations and Applications. LNCS, vol. 5600, pp. 319–334. Springer, Heidelberg (2009). doi:10.1007/978-3-642-02463-4_17
Wang, L., Shen, J., Yong, J.: A survey on bio-inspired algorithms for Web service composition. In: IEEE 16th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 569–574. IEEE (2012)
Wang, P., Ding, Z., Jiang, C., Zhou, M.: Automated Web service composition supporting conditional branch structures. Enterp. Inf. Syst. 8(1), 121–146 (2014)
Wohed, P., Aalst, W.M.P., Dumas, M., Hofstede, A.H.M.: Analysis of Web services composition languages: the case of BPEL4WS. In: Song, I.-Y., Liddle, S.W., Ling, T.-W., Scheuermann, P. (eds.) ER 2003. LNCS, vol. 2813, pp. 200–215. Springer, Heidelberg (2003). doi:10.1007/978-3-540-39648-2_18
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da Silva, A.S., Ma, H., Zhang, M., Hartmann, S. (2017). Handling Branched Web Service Composition with a QoS-Aware Graph-Based Method. In: Bridge, D., Stuckenschmidt, H. (eds) E-Commerce and Web Technologies. EC-Web 2016. Lecture Notes in Business Information Processing, vol 278. Springer, Cham. https://doi.org/10.1007/978-3-319-53676-7_12
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