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An improved DV-Hop localization algorithm based on evolutionary algorithms

Author

Listed:
  • Mahshid Mehrabi

    (Amirkabir University of Technology)

  • Hassan Taheri

    (Amirkabir University of Technology)

  • Pooria Taghdiri

    (Amirkabir University of Technology)

Abstract

Localization is one of the most important issues in wireless sensor networks and designing accurate localization algorithms is a common challenge in recent researches. Among all localization algorithms, DV-Hop attracts more attention due to its simplicity; so, we use it as a basis for our localization algorithm in order to improve accuracy. The various evolutionary algorithms such as Genetic, Shuffled Frog Leaping and Particle Swarm Optimization are employed in different phases of the main DV-Hop localization algorithm. Simulation results prove that our proposed method decreases the localization error efficiently without additional hardware.

Suggested Citation

  • Mahshid Mehrabi & Hassan Taheri & Pooria Taghdiri, 2017. "An improved DV-Hop localization algorithm based on evolutionary algorithms," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 64(4), pages 639-647, April.
    • Handle: RePEc:spr:telsys:v:64:y:2017:i:4:d:10.1007_s11235-016-0196-9
    DOI: 10.1007/s11235-016-0196-9
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    References listed on IDEAS

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    1. Stefan Tomic & Ivan Mezei, 2016. "Improvements of DV-Hop localization algorithm for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 61(1), pages 93-106, January.
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    Cited by:

    1. Gaurav Sharma & Ashok Kumar, 2018. "Improved DV-Hop localization algorithm using teaching learning based optimization for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(2), pages 163-178, February.

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    1. Gaurav Sharma & Ashok Kumar, 2018. "Improved DV-Hop localization algorithm using teaching learning based optimization for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(2), pages 163-178, February.

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