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VOL. 10, ISSUE 1 (2025)
A BWO-driven secure localization framework for wireless sensor networks
Authors
Amrin R Sheikh, Dr. Priya Vij, Dr. Sandeep Kadam
Abstract
Accurate node localization remains one of the
major research challenges in Wireless Sensor Networks (WSNs), particularly due
to environmental noise, irregular deployment structures, and limited anchor
nodes. To address these limitations, this study proposes a Black Widow
Optimization (BWO)-based localization technique designed to enhance position
accuracy through intelligent anchor selection and iterative search refinement.
The approach consists of two main phases: a distance estimation stage using
RSS-based measurements, followed by an optimization phase driven by the BWO
algorithm. The biologically inspired operators—including procreation,
cannibalism, and mutation—enable rapid convergence and improved parameter
control, ensuring effective exploration and exploitation of the search space.
The proposed method is implemented in MATLAB for a random deployment of 50
target nodes within a 100 × 100 m simulation area. Performance is evaluated
using Localization Error (LE), Localized Node Percentage (LN), and the number
of unlocalized nodes under varying anchor density, transmission range, and
iteration count. Results demonstrate that the BWO-based method significantly
outperforms Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in
both localization accuracy and robustness. Overall, the findings confirm that
BWO is an effective and computationally efficient approach for improving
localization performance in WSNs.
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Pages:14-18
How to cite this article:
Amrin R Sheikh, Dr. Priya Vij, Dr. Sandeep Kadam "A BWO-driven secure localization framework for wireless sensor networks". International Journal of Advanced Science and Research, Vol 10, Issue 1, 2025, Pages 14-18
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