Quick convergence of genetic algorithm for QoS-driven web service selection

Authors:
Yue Ma;Chengwen Zhang
Affiliations:
Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, 10 Xi Tu Cheng Road, Beijing, China;Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, 10 Xi Tu Cheng Road, Beijing, China
Venue:
Computer Networks: The International Journal of Computer and Telecommunications Networking
Year:
2008

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Abstract

A novel quickly convergent population diversity handling genetic algorithm (CoDiGA) is presented for web service selection with global Quality-of-Service (QoS) constraints. CoDiGA is characterized by good stability and quick convergence. In CoDiGA, an enhanced initial population policy and an evolution policy are proposed based on population diversity and a relation matrix coding scheme. The integration of the two policies overcomes shortcomings resulting from randomicity of genetic algorithm, such as slow convergence, great variance among the running results, soaring overhead along with increasing size of composition. The simulation results on web service selection with global QoS constraints have shown that prematurity was overcomed effectively, and convergence and stability of genetic algorithm were improved greatly.