Abstract

With the rapid growth of abundant Web services on the World Wide Web, designing effective approaches for Web service selection, which satisfy service consumers’ customized quality of service (QoS) requirement, has become a fundamental problem for the application of composed Web service. To address this problem, we propose, in this paper, a new algorithm, called Mixed Intelligent Optimization Algorithm (MIOA). MIOA optimizes service selection with multiple QoS constraints by taking advantage of both Maximum Entropy Method and Social Cognitive Optimization theory. Furthermore, Chaos method is also integrated into MIOA to improve the existing social cognitive optimization algorithm. Extensive analysis and simulations have been conducted. Our experimental results show that MIOA effectively selects high-quality service, and its convergence is also improved.

Key words: Web service, quality of service, service selection.