Web Service Selection Based on Improved Genetic Algorithm

Nowadays, Web services are becoming more and more population, and the challenge brought by Web services is dynamic selection of services. In this paper, an Improved Genetic Algorithm is proposed to solve QoS-aware service selection problem, which mainly imports an adaptive crossover, mutation strategy and also imports a terminal condition by computing variance value of the fitness of population. Experiment results show that the approach proposed in this paper can improve the efficiency of Web service selection. Although it can not only find an optimal solution, it has a better convergence speed than that of the Simple Genetic Algorithm.

[1]  Fabio Casati,et al.  Service-Oriented Computing - ICSOC 2005, Third International Conference, Amsterdam, The Netherlands, December 12-15, 2005, Proceedings , 2005, ICSOC.

[2]  Daniel A. Menascé,et al.  Optimal Service Selection Heuristics in Service Oriented Architectures , 2009, QSHINE.

[3]  Lifeng Ai,et al.  QoS-Based Web Service Composition Accommodating Inter-service Dependencies Using Minimal-Conflict Hill-Climbing Repair Genetic Algorithm , 2008, 2008 IEEE Fourth International Conference on eScience.

[4]  Daniel A. Menascé,et al.  A heuristic approach to optimal service selection in service oriented architectures , 2008, WOSP '08.

[5]  Daniel A. Menascé,et al.  On optimal service selection in Service Oriented Architectures , 2010, Perform. Evaluation.

[6]  Tao Yu,et al.  Efficient algorithms for Web services selection with end-to-end QoS constraints , 2007, TWEB.

[7]  Maria Luisa Villani,et al.  An approach for QoS-aware service composition based on genetic algorithms , 2005, GECCO '05.

[8]  Gero Mühl,et al.  QoS aggregation for Web service composition using workflow patterns , 2004 .

[9]  Darrell Whitley,et al.  A genetic algorithm tutorial , 1994, Statistics and Computing.

[10]  Maria Luisa Villani,et al.  A Lightweight Approach for QoS–Aware Service Composition , 2006 .

[11]  Tao Yu,et al.  Service selection algorithms for Web services with end-to-end QoS constraints , 2004, Proceedings. IEEE International Conference on e-Commerce Technology, 2004. CEC 2004..

[12]  Anne H. H. Ngu,et al.  QoS-aware middleware for Web services composition , 2004, IEEE Transactions on Software Engineering.

[13]  Lifeng Ai,et al.  A hybrid genetic algorithm for the optimal constrained web service selection problem in web service composition , 2010, IEEE Congress on Evolutionary Computation.

[14]  Kunal Verma,et al.  Constraint driven Web service composition in METEOR-S , 2004, IEEE International Conference onServices Computing, 2004. (SCC 2004). Proceedings. 2004.

[15]  Lalit M. Patnaik,et al.  Adaptive probabilities of crossover and mutation in genetic algorithms , 1994, IEEE Trans. Syst. Man Cybern..

[16]  Marco Aiello,et al.  Optimal QoS-Aware Web Service Composition , 2009, 2009 IEEE Conference on Commerce and Enterprise Computing.

[17]  Tao Yu,et al.  Service Selection Algorithms for Composing Complex Services with Multiple QoS Constraints , 2005, ICSOC.

[18]  E. Michael Maximilien,et al.  A framework and ontology for dynamic Web services selection , 2004, IEEE Internet Computing.

[19]  Danilo Ardagna,et al.  Adaptive Service Composition in Flexible Processes , 2007, IEEE Transactions on Software Engineering.

[20]  Liang-Jie Zhang,et al.  Requirements Driven Dynamic Services Composition for Web Services and Grid Solutions , 2004, Journal of Grid Computing.

[21]  Quan Z. Sheng,et al.  Quality driven web services composition , 2003, WWW '03.

[22]  Huaimin Wang,et al.  Quality driven Web services selection , 2005, IEEE International Conference on e-Business Engineering (ICEBE'05).