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Node Localization Based on Optimized Genetic Algorithm in Wireless Sensor Networks

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Advances in Wireless Sensor Networks (CWSN 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 501))

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Abstract

In this paper, based on an optimized genetic algorithm for node localization, a new localization algorithm is proposed by combining genetic algorithm with GPS positioning technology. The first step of the algorithm is to get the precise position of the anchor node using GPS and the part of unknown position nodes by combining with the optimized genetic algorithm. The second step is to locate other nodes by using these unknown nodes as anchor nodes. The above two steps are implemented by the following modules: the module of establishing initial population of genetic algorithm for the nodes randomly distributed in the monitoring region, the module of computing fitness value and coefficient of variation, the module of selecting optimal individual by simulating the evolutionary mechanism. Based on these modules, we optimize the whole node localization process in Wireless Sensor Networks. The experimental results demonstrate that our algorithm is efficient to locate the unknown node under the outdoor environment with the low proportion of the anchor nodes. In addition, it has the high positioning accuracy at the low cost of energy as well as the wide application.

Z. Zou—is an Associate Professor at the College of Computers, Nanjing University of Posts and Telecommunications. This project is supported by the National Natural Science Foundation of China No.61401221, Jiangsu province science and technology plan project No.BE2014718, and a Nanjing University of Posts and Telecommunication research project No.NY213037.

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Acknowledgments

This work is supported by the National Natural Science Foundation of P. R. China (Nos. 61170065, 61373137, 61171053, 61103195, 61203217), Six Industries Talent Peaks Plan of Jiangsu Province (No. 2013-DZXX-014), the Natural Science Foundation of Jiangsu Province (No. BK2012436, No. BK20141429), The Scientific and Technological Support Project (Society) of Jiangsu Province (No. BE2014718, No. BE2013666), Natural Science Key Fund for Colleges and Universities in Jiangsu Province (No. 11KJA520001, No. 12KJA520002), Scientific Research & Industry Promotion Project for Higher Education Institutions (No. JHB2012-7), the NJUPT Natural Science Foundation (No. NY213157 and No. NY213037). In addition, we are grateful to the anonymous reviewers for their insightful and constructive suggestions.

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Authors and Affiliations

  1. College of Computer, Nanjing University of Posts and Telecommunications, Nanjing, 210003, Jiangsu, China

    Zhiqiang Zou, Yinbo Lan, Shu Shen & Ruchuan Wang

  2. Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing, 210003, Jiangsu, China

    Zhiqiang Zou, Yinbo Lan, Shu Shen & Ruchuan Wang

Authors
  1. Zhiqiang Zou
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  2. Yinbo Lan
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  3. Shu Shen
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  4. Ruchuan Wang
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Corresponding author

Correspondence to Zhiqiang Zou .

Editor information

Editors and Affiliations

  1. Chinese Academy of Sciences, Beijing, China

    Limin Sun

  2. Beijing, China

    Huadong Ma

  3. Northwest University, Xi’an, China

    Dingyi Fang

  4. Northwest University, Xi’an, China

    Jinping Niu

  5. Northwest University, Xi’an, China

    Wei Wang

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Zou, Z., Lan, Y., Shen, S., Wang, R. (2015). Node Localization Based on Optimized Genetic Algorithm in Wireless Sensor Networks. In: Sun, L., Ma, H., Fang, D., Niu, J., Wang, W. (eds) Advances in Wireless Sensor Networks. CWSN 2014. Communications in Computer and Information Science, vol 501. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46981-1_19

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  • DOI: https://doi.org/10.1007/978-3-662-46981-1_19

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46980-4

  • Online ISBN: 978-3-662-46981-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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