An Adaptive Approach for QoS-Aware Web Service Composition Using Cultural Algorithms

• Published in: AI 2007: Advances in Artificial Intelligence Vol. 4830; pp. 140 - 149
• Main Authors: Kobti, Ziad, Zhiyang, Wang
• Format: Book Chapter
• Language: English
• Published: Germany Springer Berlin / Heidelberg 2007; Springer Berlin Heidelberg
• Series: Lecture Notes in Computer Science
• Subjects: Artificial intelligence; cultural algorithms; Data mining; genetic algorithms; Mathematical theory of computation; quality of service (QoS); web service composition
• ISBN: 9783540769262; 3540769269
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-540-76928-6_16

Web service composition is the process of integrating existing web services. It is a prospective method to build an application system. The current approaches, however, only take service function aspect into consideration. With the rapid growth of web service applications and the abundance of service providers, the consumer is facing the inevitability of selecting the “maximum satisfied” service providers due to the dynamic nature of web services. This requirement brings us some research challenges including web service quality model, the design of web service framework monitoring service real time quality. The further challenge is to find the algorithm which can handle customized service quality parameters and has good performance to solve NP-hard web services global selection problem. In this paper, we propose an adaptive web service framework using an extensible service quality model. Evolutionary algorithms are adopted to accelerate service global selection. We report on the comparison between Cultural Algorithms with Genetic Algorithms and random service selection.