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An Improved Node Localization Method for Wireless Sensor Network Based on PSO and Evaluation of Environment Variables

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Advances in Swarm Intelligence (ICSI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9713))

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Abstract

Node localization is an essential problem for some engineering applications in wireless sensor network (WSN). The problem characteristics of node localization in WSN are analyzed firstly, and then a framework and a strategy for the settings of important parameters are given to solve such problems with particle swarm optimization (PSO). Furthermore, the environment variable of WSN is evaluated and an improved node localization method of wireless sensor network based on PSO is proposed. In the proposed node localization method, the environment variable of WSN is evaluated during the process of ranging and the fitness function is designed according to the environment variable, and then the PSO algorithm is adopted to solve the node localization problem. Compared with the traditional methods, the experiments results show that the proposed method has good performance. Besides, we also discussed the relationship among the number of nodes, the number of failure nodes, the positioning error and the mean distance-measuring error.

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Acknowledgements

This paper is supported by the Fundamental Research Funds for the Central Universities.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Southeast University, Nanjing, China

    Qingjian Ni

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  1. Qingjian Ni
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Correspondence to Qingjian Ni .

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Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Shenzen University, Shenzhen, China

    Li Li

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© 2016 Springer International Publishing Switzerland

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Ni, Q. (2016). An Improved Node Localization Method for Wireless Sensor Network Based on PSO and Evaluation of Environment Variables. In: Tan, Y., Shi, Y., Li, L. (eds) Advances in Swarm Intelligence. ICSI 2016. Lecture Notes in Computer Science(), vol 9713. Springer, Cham. https://doi.org/10.1007/978-3-319-41009-8_35

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  • DOI: https://doi.org/10.1007/978-3-319-41009-8_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41008-1

  • Online ISBN: 978-3-319-41009-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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