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Node Localization Method in Wireless Sensor Networks Using Combined Crow Search and the Weighted Centroid Method.

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  • 1Department of Computer Science, King Faisal University, Al Hofuf P.O. Box 400, Saudi Arabia.

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Summary
This summary is machine-generated.

This study introduces the Crow Search Weighted Centroid Localization (CS-WCL) algorithm for efficient wireless sensor network (WSN) node localization. CS-WCL significantly reduces average localization error and energy consumption compared to existing methods.

Keywords:
anchor nodescrow search algorithmlocalizationrange free

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Area of Science:

  • Wireless Sensor Networks (WSNs)
  • Localization Algorithms
  • Nature-Inspired Computing

Background:

  • Node localization in WSNs is crucial but faces challenges like anchor node selection, limited energy, and computational intensity.
  • Existing localization methods, including single-anchor and multiple-anchor techniques, suffer from issues like co-linearity, high computational cost, and significant localization errors.
  • Nature-inspired algorithms offer potential but often exhibit long processing times, high power consumption, and sensitivity to parameter selection.

Purpose of the Study:

  • To develop a more efficient and trustworthy node localization algorithm for WSNs.
  • To improve the accuracy of node localization while reducing energy consumption.
  • To address the limitations of existing localization techniques, particularly regarding anchor node selection and computational overhead.

Main Methods:

  • A novel Crow Search Weighted Centroid Localization (CS-WCL) algorithm was developed.
  • The Crow Search Algorithm was employed for optimal selection of anchor nodes from a population.
  • The Weighted Centroid Method was utilized for precise localization of unknown nodes.

Main Results:

  • CS-WCL demonstrated a reduced Average Localization Error (ALE) of 15% compared to WCL and DV-Hop, across varying communication radii (20m-45m).
  • Scalability tests showed CS-WCL reduced ALE to 2.59% (from 28.75%) with varying beacon nodes (3 to 2).
  • Energy consumption was significantly reduced, from 120mJ to 45mJ, for network sizes ranging from 30 to 300 nodes, outperforming WCL and DV-Hop.

Conclusions:

  • The CS-WCL algorithm offers a more efficient and reliable solution for node localization in WSNs.
  • CS-WCL effectively minimizes localization errors and conserves energy compared to conventional and other nature-inspired methods.
  • The proposed algorithm shows superior performance and scalability, validated using MATLAB 2022b.