Abstract
Web services composition has gained a considerable momentum as a means to create and streamline B2B collaborations within and across organizational boundaries. This paper focuses on the web services composition and provides a novel selection algorithm based on global QoS optimizing and Multi-objective Chaos Ant Colony Optimization (MOCACO). Firstly, the web services selection model with QoS global optimization is converted into a multi-objective optimization problem. Furthermore, the MOCACO is used to select the service and optimize QoS to satisfy the user constraints. During the optimizing procedure, the random and ergodic chaos variable is used to make an optimal search, it overcomes the problem of low efficiency and easily being in a partial optimization that ant colony algorithm brings. The simulation shows that the MOCACO is more efficient and effective than Multi-objective Genetic Algorithm (MOGA) applied to services composition.
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References
Kleijnen, S., Raju, S.: An Open Web services Architecture, pp. 38–46. ACM Press, NewYork (2003)
Jorge, C., Amit, S., John, M.: Quality of Service for workflows and Web Service Processes. Journal of Web Semantics 1(3), 281–338 (2004)
Liu, Y.T., Anne, H.H., Zeng, L.Z.: QoS Computation and Policing in Dynamic Web Services selection. In: Proc. WWW 2004, pp. 66–73. ACM, New York (2004)
Wan, L., Gao, C., Xiao, W., Su, L. (eds.): Global optimization method of Web services composition based on QoS, Computer Engineer And Applications, vol. 24 (2007)
Liu, S., Liu, Y., Jing, N., Tang, G., Tang, Y.: A Dynamic Web Service Selection Strategy with QoS Global Optimization Based on Multi-objective Genetic Algorithm. In: Zhuge, H., Fox, G.C. (eds.) GCC 2005. LNCS, vol. 3795, pp. 84–89. Springer, Heidelberg (2005)
Schaerer, M., Barán, B.: A Multi-objective Ant Colony System For Vehicle Routing Problem With Time Windows. In: Proc. IASTED International Conference on Applied Informatics, Innsbruck (2003)
Yang, H., Wang, H., Hou, L., Sun, X. (eds.): Application of Chaos Ant Colony Optimization in the Intelligent Transportation System and Its Algorithm. Journal Of Chengdu University (Natural Science Edition) 4 (2007)
Qiqing, F., Xiaoming, P., Qinghua, L., Yahui, H.: A Global QoS Optimizing Web Services Selection Algorithm based on MOACO for Dynamic Web Service Composition. In: 2009 International Forum on Information Technology and Applications, pp. 37–42 (2009)
Van Veldhuizen, D.A.: Multiobjective Evolutionary Algorithms: Classifications, Analyses and New Innovations. Ph. D. thesis Air Force Institute of Technology (1999)
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Li, W., Yan-xiang, H. (2010). A Web Service Composition Algorithm Based on Global QoS Optimizing with MOCACO. In: Hsu, CH., Yang, L.T., Park, J.H., Yeo, SS. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2010. Lecture Notes in Computer Science, vol 6082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13136-3_22
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DOI: https://doi.org/10.1007/978-3-642-13136-3_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13135-6
Online ISBN: 978-3-642-13136-3
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