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Nodes Deployment Optimization Algorithm Based on Fuzzy Data Fusion Model in Wireless Sensor Networks

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Advanced Data Mining and Applications (ADMA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11888))

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Abstract

As an integrated network, wireless sensor networks can connect the logic information world with the real physical world by performing information sensing, gathering, processing and delivering. There are diverse and potential applications for Wireless sensor networks. In recent years, the increasing requisitions of Wireless sensor networks have more and more research dedicated to the question of sensor nodes deployment. As for the nodes deployment of underwater wireless sensor networks, the optimization strategy on node deployment determines the capability and quality of service of Wireless sensor networks as well. There are some key points that should be considered, including the coverage range to be monitored, energy consumption of nodes, amount of deployed sensors, connectivity, and lifetime of the Wireless sensor networks. This paper analyzes the problem of nodes deployment optimization in wireless sensor network. Referring to the fuzzy cognitive model and fuzzy data fusion model, with consideration of certain environmental factors which may affect the detection result, a novel method NAFC is presented in this paper. The simulation model is established by MATLAB software. According to the simulation results, the demonstrated algorithm of underwater sensor node deployment shows its effectiveness, which can fulfill the requisition of network coverage ratio, reduce the number of deployed nodes, prolong the network lifetime and expand the detection range of network, thus the scheme improve the comprehensive detection performance of WSN accordingly.

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Authors and Affiliations

  1. Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China

    Na Li & Qiangyi Li

  2. Henan University of Science and Technology, Luoyang, 471023, Henan, China

    Qiangyi Li & Qiangnan Li

Authors
  1. Na Li
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  2. Qiangyi Li
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Corresponding author

Correspondence to Qiangyi Li .

Editor information

Editors and Affiliations

  1. Deakin University, Burwood, VIC, Australia

    Jianxin Li

  2. The University of Queensland, St. Lucia, QLD, Australia

    Sen Wang

  3. Flinders University, Bedford Park, SA, Australia

    Shaowen Qin

  4. Dalian Neusoft University of Information, Dalian, China

    Xue Li

  5. Beijing Institute of Technology, Beijing, China

    Shuliang Wang

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Li, N., Li, Q., Li, Q. (2019). Nodes Deployment Optimization Algorithm Based on Fuzzy Data Fusion Model in Wireless Sensor Networks. In: Li, J., Wang, S., Qin, S., Li, X., Wang, S. (eds) Advanced Data Mining and Applications. ADMA 2019. Lecture Notes in Computer Science(), vol 11888. Springer, Cham. https://doi.org/10.1007/978-3-030-35231-8_55

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  • DOI: https://doi.org/10.1007/978-3-030-35231-8_55

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-35230-1

  • Online ISBN: 978-3-030-35231-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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