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Localization of sensor nodes in wireless sensor networks using bat optimization algorithm with enhanced exploration

Satinder Singh Mohar1, Sonia Goyal1, Ranjit Kaur1

  • 1Department of Electronics and Communication Engineering, Punjabi University Patiala, Punjab, India.

The Journal of Supercomputing
|February 28, 2022
PubMed
Summary

Two new bat optimization algorithm (BOA) variants improve wireless sensor network (WSN) localization accuracy and efficiency. Variant 2 demonstrates superior performance over original BOA and other methods, reducing localization errors and computation time.

Keywords:
Bat optimization algorithmComputation timeLocalization errorNode localizationTarget nodes

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Accurate localization of sensor nodes in wireless sensor networks (WSNs) is crucial for applications like military surveillance.
  • The original bat optimization algorithm (BOA) can get trapped in local optima, limiting its effectiveness for node localization.
  • Existing localization methods often struggle with accuracy and efficiency in complex WSN environments.

Purpose of the Study:

  • To propose two enhanced variants of the bat optimization algorithm (BOA) for more efficient sensor node localization in WSNs.
  • To address the limitations of the original BOA, specifically its tendency to get stuck in local optimum solutions.
  • To improve the exploration and exploitation capabilities of the BOA for better localization accuracy and speed.

Main Methods:

  • Development of two modified bat optimization algorithm (BOA) variants (Variant 1 and Variant 2) with improved global and local search strategies.
  • Extensive simulations were conducted using varying numbers of target and anchor nodes to evaluate algorithm performance.
  • Comparison of the proposed BOA variants against the original BOA and other established optimization algorithms for node localization.

Main Results:

  • The proposed BOA variants 1 and 2 significantly outperformed the original BOA and other existing algorithms in terms of mean localization error, number of localized nodes, and computation time.
  • Variant 2 of the proposed BOA demonstrated superior performance compared to Variant 1 and the original BOA across various error metrics and localization efficiencies.
  • The proposed BOA variant 2 achieved lower mean localization error and required less computation time, indicating higher effectiveness.

Conclusions:

  • The enhanced bat optimization algorithm variants offer a more efficient and accurate solution for sensor node localization in wireless sensor networks.
  • BOA variant 2 is identified as the most effective method, surpassing other algorithms in accuracy and computational speed.
  • The proposed approach provides a robust solution for critical WSN applications requiring precise node positioning.