Optimizing Energy Constrained Target Localization and Tracking with Radial Bias and Seeker Optimization Algorithms in Wireless Sensor Networks DOI Creative Commons

S. Yazhinian,

S. Famila,

P Jose

et al.

MethodsX, Journal Year: 2025, Volume and Issue: unknown, P. 103280 - 103280

Published: March 1, 2025

The standard localization approach is characterized by a fixed position distribution of the anchor nodes, which cannot be dynamically modified based on deployment environment. This paper proposes novel combining Radial Bias (RB) with Seeker Optimization Algorithm (SOA) to address challenges energy-constrained target and tracking. RB technique enhances accuracy refining estimates target, while SOA optimizes sensor data transmission paths minimize energy consumption. By integrating these two methodologies, ensures balance between precision in tracking efficiency. Extensive simulations shown this surpasses existing methods terms both determining location duration network operation. makes it attractive option for applications WSNs. investigation examines outcome particle count RBSO algorithm, specifically values 5, 10, 15, 20, 25. simulation results show that recommended strategy decreases particles, speeds up positioning tracking, maintains accuracy. It seen proposed RadB_SOA achieves 12.4 % error, 14.6 ranging 96.3 coverage, 98.65 PDR, 21.56 consumption.•The Bias-Seeker (RadB_SOA) suggested usage wireless networks.•Simulation outcomes reveal improved accuracy, minimized errors, as well increased coverage over current techniques.•The research presents an extensive evaluation fluctuations RBSO, demonstrating enhanced speed

Language: Английский

Optimizing Energy Constrained Target Localization and Tracking with Radial Bias and Seeker Optimization Algorithms in Wireless Sensor Networks DOI Creative Commons

S. Yazhinian,

S. Famila,

P Jose

et al.

MethodsX, Journal Year: 2025, Volume and Issue: unknown, P. 103280 - 103280

Published: March 1, 2025

The standard localization approach is characterized by a fixed position distribution of the anchor nodes, which cannot be dynamically modified based on deployment environment. This paper proposes novel combining Radial Bias (RB) with Seeker Optimization Algorithm (SOA) to address challenges energy-constrained target and tracking. RB technique enhances accuracy refining estimates target, while SOA optimizes sensor data transmission paths minimize energy consumption. By integrating these two methodologies, ensures balance between precision in tracking efficiency. Extensive simulations shown this surpasses existing methods terms both determining location duration network operation. makes it attractive option for applications WSNs. investigation examines outcome particle count RBSO algorithm, specifically values 5, 10, 15, 20, 25. simulation results show that recommended strategy decreases particles, speeds up positioning tracking, maintains accuracy. It seen proposed RadB_SOA achieves 12.4 % error, 14.6 ranging 96.3 coverage, 98.65 PDR, 21.56 consumption.•The Bias-Seeker (RadB_SOA) suggested usage wireless networks.•Simulation outcomes reveal improved accuracy, minimized errors, as well increased coverage over current techniques.•The research presents an extensive evaluation fluctuations RBSO, demonstrating enhanced speed

Language: Английский

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