A web service composition algorithm based on global QoS optimizing with MOCACO

被引：0
作者：
Li W. [1 ]
He Y.-X. [1 ]
机构：
[1] Computer School, Wuhan University, Wuhan
来源：
Advances in Intelligent and Soft Computing | 2011年 / 111卷
基金：
中国博士后科学基金;
关键词：
ant colony algorithm; chaos operator; multi-objecctive; QoS; web services composition;
D O I：
10.1007/978-3-642-25188-7_10
中图分类号：
学科分类号：
摘要：
Web services composition has gained a considera-ble momentum as a means to create and streamline B2B collabo- rations 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. Further-more, the MOCACO is used to select the service and optimize QoS to satisfy the user constraints. During the optimizing proce-dure, 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. © 2011 Springer-Verlag Berlin Heidelberg.
引用
收藏
页码：79 / 86
页数：7
相关论文
共 9 条
  • [1] Kleijnen S., Raju S., An Open Web Services Architecture, pp. 38-46, (2003)
  • [2] Jorge C., Amit S., John M., Quality of service for workflows and web service processes, Journal of Web Semantics, 1, 3, pp. 281-338, (2004)
  • [3] Liu Y.T., Anne H.H., Zeng L.Z., QoS computation and policing in dynamic web services selection, Proc. WWW 2004, pp. 66-73, (2004)
  • [4] Wan L., Gao C., Xiao W., Su L., Global optimization method of Web services composition based on QoS, Computer Engineer And Applications, 24, (2007)
  • [5] 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, 3795, pp. 84-89, (2005)
  • [6] Schaerer M., Baran B., A multi-objective ant colony system for vehicle routing problem with time windows, Proc. IASTED International Conference on Applied Informatics, (2003)
  • [7] Yang H., Wang H., Hou L., Sun X., Application of chaos ant colony optimization in the intelligent transportation system and its algorithm, Journal Of Chengdu University, 4, (2007)
  • [8] Fang Q., Peng X., Liu Q., Hu Y., A global QoS optimizing web services selection algorithm based on moaco for dynamic web service composition, 2009 International Forum on Information Technology and Applications, pp. 37-42, (2009)
  • [9] Van Veldhuizen D.A., Multiobjective Evolutionary Algorithms: Classifications Analyses and New Innovations, (1999)
1