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Knowledge based differential evolution for cloud computing service composition

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Abstract

Web service composition problem has been a hot topic recently. With the development of cloud computing technology, a single Web service can no longer meet the users’ requirement. However, service composition gives a proper way to solve this problem. A knowledge based differential evolution algorithm for Web service composition was proposed in this paper. Firstly, we introduce QoS evaluation models, and propose the mathematical model of QoS applied to Web service composition optimizing problem. Secondly, we present a knowledge based differential evolution algorithm used to solve Web service composition optimizing problem. The algorithm improves the accelerate convergence velocity by importing structure knowledge. Finally, simulation experiments and evaluation methodology are given, and the results prove KDE has better performance in Web service composition problem, compared with original DE, PSO.

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Acknowledgements

This paper was supported by Natural Science Foundation of Jiangsu Province of China (No. BK20160910, BK20140883), China Postdoctoral Science Foundation funded project (No. 2015M571790, 2015M581844), Jiangsu Planned Projects for Postdoctoral Research Funds (1501125B), NUPTSF (Grant Nos. NY213047, NY213050, NY214102, NY214098), Natural science fund for colleges and universities in Jiangsu Province (No. 16KJB520034), A Project Funded by the Priority Academic Program Development of Jiangsu Higer Education Institutions (PAPD), Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET).

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Correspondence to Jin Qi or Yanfei Sun.

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Qi, J., Xu, B., Xue, Y. et al. Knowledge based differential evolution for cloud computing service composition. J Ambient Intell Human Comput 9, 565–574 (2018). https://doi.org/10.1007/s12652-016-0445-5

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