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Robust evaluation method of communication network based on the combination of complex network and big data

  • S.I. : ATCI 2020
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Abstract

The essence of big data may be the science of complex network, which should be one of the basic theories of big data, and the direct object of mobile communication network is big data. The purpose of this paper is to study the evaluation method of communication network robustness based on the combination of cloud edge computer and big data. Firstly, the technical system of big data technology and the basic concept and model of complex network are studied. Secondly, it analyzes the robustness of single-layer network and multi-layer network to lay a solid foundation for the following experiments. Set up the experiment code, and test each experiment several times to get the final data. The experimental results show that the change of R (LCC) from 0 to non-0 occurs at the reciprocal of the average for different network averages, that is, the critical value of network robustness P is equal to the reciprocal of the average. Random networks are not robust to regular networks. Even if the average order of the random network is the same as that of the regular network, the random network is not robust to the regular network. There are 5 × 104 nodes in each of the random networks ER1 and ER2. ER1 and ER2 are one to one connected. The average value of ER1 is set to be the same as the average value of ER2. The multi-layer random network is not stable without single-layer random network.

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Acknowledgements

This work was supported by the Natural Science Foudation of Hunan Province, China (No. 2017JJ2237). Author wishes to express gratitude to the Aid Program for Science and Technology Innovative Research Team in Higher Educational Institution of Hunan Province. This work was supported by Public Projects of Wenzhou Science & Technology Bureau (Grant Nos. G20150020 & G20160007) and also supported by Zhejiang public welfare technology application research project (No. LGG19F020004).

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Authors and Affiliations

  1. Provincial Key Laboratory of Informational Service for Rural Area of Southwestern Hunan, Shaoyang University, Shaoyang, 422000, Hunan, China

    Chengshun Huang

  2. College of Information Engineering, Shaoyang University, Shaoyang, 422000, Hunan, China

    Chengshun Huang

  3. School of Computer Engineering, Hubei University of Arts and Science, Xiangyang, 441053, Hubei, China

    Li Zhu

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  1. Chengshun Huang
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  2. Li Zhu
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Correspondence to Li Zhu.

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Huang, C., Zhu, L. Robust evaluation method of communication network based on the combination of complex network and big data. Neural Comput & Applic 33, 887–896 (2021). https://doi.org/10.1007/s00521-020-05264-0

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