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A Genertic Algorithm Application on Wireless Sensor Networks

  • Conference paper
Modern Advances in Applied Intelligence (IEA/AIE 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8481))

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Abstract

The Genetic Algorithm (GA) is performed in the Base Station (BS) to generate the optimal clusters and cluster heads for a given Wireless Sensor Networks. And then, Dijkstra’s algorithm is used to generate the energy-efficient routing paths based on the optimal cluster heads produced by the GA. In addition, we use the concept of data aggregation to eliminate the redundant data. To demonstrate the feasibility of our approach, formal analysis and experimental results are presented.

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References

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Author information

Authors and Affiliations

  1. Jodrey School of Computer Science, Acadia University, Wolfville, Canada

    Haiyi Zhang & Yifei Jiang

Authors
  1. Haiyi Zhang
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  2. Yifei Jiang
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Texas State University, TX 78666, San Marcos, USA

    Moonis Ali

  2. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, No. 415, Chien Kung Road, 80778, Kaohsiung, Taiwan

    Jeng-Shyang Pan

  3. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan

    Shyi-Ming Chen

  4. Department of Electronics Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan (ROC)

    Mong-Fong Horng

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© 2014 Springer International Publishing Switzerland

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Zhang, H., Jiang, Y. (2014). A Genertic Algorithm Application on Wireless Sensor Networks. In: Ali, M., Pan, JS., Chen, SM., Horng, MF. (eds) Modern Advances in Applied Intelligence. IEA/AIE 2014. Lecture Notes in Computer Science(), vol 8481. Springer, Cham. https://doi.org/10.1007/978-3-319-07455-9_12

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  • DOI: https://doi.org/10.1007/978-3-319-07455-9_12

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07454-2

  • Online ISBN: 978-3-319-07455-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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