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Energy-Efficient Clustering and Localization Technique Using Genetic Algorithm in Wireless Sensor Networks

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  • Junfeng Chen
  • Samson Hansen Sackey
  • Joseph Henry Anajemba
  • Xuewu Zhang
  • Yurun He
  • Abd E.I.-Baset Hassanien

Abstract

Localization is recognized among the topmost vital features in numerous wireless sensor network (WSN) applications. This paper puts forward energy-efficient clustering and localization centered on genetic algorithm (ECGAL), in which the residual energy, distance estimation, and coverage connection are developed to form the fitness function. This function is certainly fast to run. The proposed ECGAL exhausts a lesser amount of energy and extends wireless network existence. Finally, the simulations are carried out to assess the performance of the proposed algorithm. Experimental results show that the proposed algorithm approximates the unknown node location and provides minimum localization error.

Suggested Citation

  • Junfeng Chen & Samson Hansen Sackey & Joseph Henry Anajemba & Xuewu Zhang & Yurun He & Abd E.I.-Baset Hassanien, 2021. "Energy-Efficient Clustering and Localization Technique Using Genetic Algorithm in Wireless Sensor Networks," Complexity, Hindawi, vol. 2021, pages 1-12, August.
    • Handle: RePEc:hin:complx:5541449
    DOI: 10.1155/2021/5541449
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