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A Segmented Path Heuristic Recovery Algorithm for WSNs Based on Mobile Sink

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Computer Supported Cooperative Work and Social Computing (ChineseCSCW 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1681))

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Abstract

Mobile sink can effectively solve hot issues in wireless sensor networks (WSNs), but its mobility will lead to changes in network topology and unreliable transmission links. By analyzing various efficient energy-saving and fault-tolerant routing methods, a dynamic segmented path heuristic recovery algorithm for WSNs based on mobile sink is proposed. The data transmission path is divided into anterior segment path and posterior segment path, and the whale optimization algorithm is used to recover the posterior segment path. The fitness function of the posterior segment path recovery is constructed, considering the residual energy, node distance, node energy consumption and delay. The performance of the proposed algorithm is evaluated and the whale heuristic algorithm is used to efficiently recover the posterior segment path in different dimensions. Analysis and simulation experiments show that the segmented path recovery method can effectively save path energy consumption and delay, and the whale recovery algorithm is simple and effective.

Supported by Supported by Shanxi Provine Natural Science fund project (201901D111311), Key R &D projects in Datong city(2020023),and Datong University project(2019k5).

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Acknowledgements

This work was supported by Shanxi Provine Natural Science fund project (20190-1D111311), Key R & D projects in Datong city(2020023), and Datong University project(2019k5).

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Authors and Affiliations

  1. School of Computer and Network Engineering, Shanxi Datong University, Datong, China

    Nie Wenmei, Song Xiaoxia, Li Yong & Zhang Xulong

Authors
  1. Nie Wenmei
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  2. Song Xiaoxia
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  3. Li Yong
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  4. Zhang Xulong
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Corresponding author

Correspondence to Song Xiaoxia .

Editor information

Editors and Affiliations

  1. Shandong University, Jinan, China

    Yuqing Sun

  2. Fudan University, Shanghai, China

    Tun Lu

  3. Taiyuan University of Science and Technology, Taiyuan, China

    Yinzhang Guo

  4. Shanxi Datong University, Datong, China

    Xiaoxia Song

  5. Tongji University, Shanghai, China

    Hongfei Fan

  6. Guangdong University of Technology, Guangzhou, China

    Dongning Liu

  7. University of Shanghai for Science and Technology, Shanghai, China

    Liping Gao

  8. Tongji University, Shanghai, China

    Bowen Du

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Wenmei, N., Xiaoxia, S., Yong, L., Xulong, Z. (2023). A Segmented Path Heuristic Recovery Algorithm for WSNs Based on Mobile Sink. In: Sun, Y., et al. Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2022. Communications in Computer and Information Science, vol 1681. Springer, Singapore. https://doi.org/10.1007/978-981-99-2356-4_27

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  • DOI: https://doi.org/10.1007/978-981-99-2356-4_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-2355-7

  • Online ISBN: 978-981-99-2356-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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