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Research on QoS service composition based on coevolutionary genetic algorithm

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Abstract

Traditional genetic algorithms overemphasize the struggle for survival and neglect all other aspects of biology. In addition, binary encoding is widely used in individual coding. Since the individual chromosomes produced are longer in length, it is difficult to ensure the efficiency of the algorithm. In this study, a coevolutionary genetic algorithm is proposed for web service composition based on quality of service (QoS), which fully considers the individual relationships among populations. The real coding method is adopted to solve the service selection problem based on QoS, so that the negative effect of the long length of chromosomes in the algorithm is avoided. Moreover, in view of the difficulty of determining the weight of each QoS attribute in web services, we propose to use the entropy method to determine the weights of each one. Compared with the traditional genetic algorithm, the experimental results show that the proposed algorithm converges faster in the service composition, and the fitness of the optimal solution is higher.

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Acknowledgements

This work has been supported by the National Natural Science Foundation of China (Grant No. 61772070), the National Key Research and Development Program of China (Grant Nos. 2016YFB0800700, 2016YFC060090), Excellent Teachers Development Foundation of BUCEA, the Fundamental Research Funds for Beijing Universities of Civil Engineering and Architecture.

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Authors and Affiliations

  1. School of Computer, Beijing Institute of Technology, Beijing, People’s Republic of China

    Yuanzhang Li, Jingjing Hu, Zhuozhuo Wu & Chen Liu

  2. Library, Beijing University of Posts and Telecommunications, Beijing, People’s Republic of China

    Feifei Peng

  3. School of Electrical and Information Engineering and Beijing Key Laboratory of Intelligent Processing for Building Big Data, Beijing University of Civil Engineering and Architecture, Beijing, People’s Republic of China

    Yu Zhang

  4. State Key Laboratory in China for GeoMechanics and Deep Underground Engineering (Beijing), China University of Mining & Technology, Beijing, People’s Republic of China

    Yu Zhang

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  1. Yuanzhang Li
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  2. Jingjing Hu
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  3. Zhuozhuo Wu
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  4. Chen Liu
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  5. Feifei Peng
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  6. Yu Zhang
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Correspondence to Jingjing Hu.

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Communicated by B. B. Gupta.

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Li, Y., Hu, J., Wu, Z. et al. Research on QoS service composition based on coevolutionary genetic algorithm. Soft Comput 22, 7865–7874 (2018). https://doi.org/10.1007/s00500-018-3510-5

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