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An improved intelligent clustering algorithm for irregular wireless network

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Abstract

The topology management classifiers consist of several methods, such as the typical clustering-based method excelled in wireless network partitioning. However, most algorithms appear load unbalanced in the application of irregular network, resulting “energy hot zone” phenomenon. This paper proposes an improved intelligent clustering algorithm and applies it to the complex water system environment. Firstly, we build a new energy consumption model for wireless transmission network, and design a genetic clustering strategy via the minimum energy consumption principle. Secondly, we introduce the P matrix coding approach considering the search scale, so as to avoid the squared increasing relationship between the searching space and the data calculation. Thirdly, we employ adaptive genetic operator to enhance the directivity of the searching space, and utilize a fuzzy modified operator to enhance the accuracy of the cluster head selection, which may ensure the iterative efficiency. Through numerical simulations, empirical results show better performance than traditional methods in load balancing and clustering efficiency, which can effectively improve the network convergence speed and extend the network lifetime.

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Acknowledgements

This paper is sponsored by Key Research and Development Program of Shaanxi province in 2017 (NO.2017GY-085).This paper is sponsored by National Natural Science Foundation of China (NO.61906086).

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Authors and Affiliations

  1. Xi’an Technological University, No. 2 Xuefuzhonglu Road, Weiyang District, Xi’an City, Shaanxi Province, China

    Xiang Hua, Zhaoxin Dong, Hongjuan Yao, Zhao Wang, Baohua Li & Bingqing Jiang

  2. Shaanxi Normal University, No. 620, West Chang’an Avenue, Xi’an City, Shaanxi Province, China

    Hongtao Liang

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  1. Xiang Hua
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  2. Zhaoxin Dong
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  3. Hongjuan Yao
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  4. Zhao Wang
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  5. Baohua Li
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  7. Hongtao Liang
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Correspondence to Xiang Hua.

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Hua, X., Dong, Z., Yao, H. et al. An improved intelligent clustering algorithm for irregular wireless network. Wireless Netw 28, 949–963 (2022). https://doi.org/10.1007/s11276-019-02217-x

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