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PSLDV-Hop: a robust localization algorithm for WSN using PSO and refinement process.

Bhupinder Kaur1, Deepak Prashar1, Arfat Ahmad Khan2

  • 1School of Computer Science & Engineering, Lovely Professional University, Phagwara, Punjab, India.

Peerj. Computer Science
|September 24, 2025
PubMed
Summary
This summary is machine-generated.

Wireless sensor networks (WSNs) require accurate node localization for security and monitoring. The new PSLDV-Hop algorithm improves distance vector hop localization accuracy by integrating particle swarm optimization, significantly reducing errors.

Keywords:
AILocalizationLocalization ErrorOptimizationSensor NodesWSN

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Area of Science:

  • Wireless Sensor Networks (WSNs)
  • Localization Algorithms
  • Optimization Techniques

Background:

  • WSNs are crucial for security, surveillance, and environmental monitoring.
  • Accurate sensor node localization is essential for WSNs to function effectively.
  • Existing localization algorithms, like Distance Vector Hop (DV-Hop), face challenges with accuracy due to hop count estimations.

Purpose of the Study:

  • To develop an improved localization algorithm for WSNs that enhances accuracy.
  • To address the limitations of the standard DV-Hop algorithm in sensor node positioning.
  • To integrate Particle Swarm Optimization (PSO) with DV-Hop for more precise localization.

Main Methods:

  • Proposed an enhanced algorithm, PSLDV-Hop, combining DV-Hop with PSO and a refinement procedure.
  • Utilized exact anchor node coordinates and fractional hop counts to correct estimated distances.
  • Employed an iterative evolution algorithm for improved localization accuracy.

Main Results:

  • PSLDV-Hop demonstrated superior performance compared to classical algorithms and the original DV-Hop.
  • Significant percentage improvements in localization accuracy were observed, especially at larger communication ranges (e.g., 65% improvement at range 40).
  • The algorithm consistently outperformed PSO-DV-Hop and GA-DV-Hop across various communication ranges (20, 30, 40 units).

Conclusions:

  • The PSLDV-Hop algorithm effectively reduces localization errors in WSNs.
  • Integrating PSO with DV-Hop offers a significant advancement in achieving higher accuracy for node localization.
  • PSLDV-Hop presents a robust and accurate solution for WSN localization challenges.