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Optimization of range based self-localization problem in wireless sensor networks using improved cuckoo search

Srilakshmi Aouthu¹, N Dhanalakshmi², T Seshagiri³

¹Electronics and Communication Engineering Department, Vasavi College of Engineering, Hyderabad, 500031, Telangana, India.

Scientific Reports

|November 13, 2025

Summary

A novel weight-based anchor node selection strategy improves wireless sensor network (WSN) localization accuracy. This method enhances target node (TN) positioning using an improved cuckoo search algorithm, reducing errors and costs.

Keywords:

Anchor node Localization Localization accuracy Range-based localization Wireless sensor network

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Area of Science:

Wireless Sensor Networks (WSNs)
Localization Algorithms
Optimization Techniques

Background:

Self-localization in WSNs estimates target node (TN) coordinates using known anchor node (AN) positions.
Accurate TN localization is crucial for location-aware applications, including tracking, healthcare, and traffic monitoring.
Existing localization algorithms face challenges with noise and anisotropic network conditions.

Purpose of the Study:

To propose a weight-based anchor node (AN) selection strategy for enhancing WSN localization accuracy.
To mitigate noise effects from spatial and temporal variations using distance-based AN weighting.
To compute optimal TN location coordinates using an improved cuckoo search algorithm.

Main Methods:

A weight-based AN selection strategy utilizing only four GPS-enabled ANs.
Assigning weights to ANs based on their distance to the TN to reduce noise.
Employing an improved cuckoo search algorithm for global optimal coordinate computation in anisotropic WSNs.

Main Results:

The proposed CERBLA algorithm achieved a localization accuracy of 99.24% with a range measurement error of 1.18 m.
Localization accuracy was significantly enhanced compared to existing algorithms (e.g., DCK-GWO, WOA-QT, ECS-NL).
Superior performance was observed, especially with fewer than ten ANs, indicating cost-effectiveness.

Conclusions:

The proposed weight-based AN selection strategy and improved cuckoo search algorithm effectively enhance WSN localization accuracy.
The CERBLA algorithm offers a robust and accurate solution for WSN localization, outperforming several state-of-the-art methods.
This approach is particularly suitable for cost-effective indoor localization applications in WSNs.