nodeWSNsec: A hybrid metaheuristic approach for reliable security and node deployment in WSNs
Rahul Mishra, Sudhanshu Kumar Jha, Naresh Kshetri, Bishnu Bhusal, Mir Mehedi Rahman, Md Masud Rana, Aimina Ali Eli, Khaled Aminul Islam, Bishwo Prakash Pokharel

TL;DR
This paper introduces a hybrid metaheuristic combining GA and PSO for efficient, reliable node deployment in WSNs, significantly reducing sensor count while maintaining coverage and connectivity.
Contribution
It presents a novel hybrid GA-PSO approach that outperforms standalone algorithms and CMOMPA in WSN deployment, balancing exploration and convergence.
Findings
Requires 15-25% fewer sensor nodes
Maintains 95% or more area coverage
Outperforms CMOMPA in coverage and deployment time
Abstract
Efficient and reliable node deployment in Wireless Sensor Networks is crucial for optimizing coverage of the area, connectivity among nodes, and energy efficiency. This paper proposes a hybrid meta heuristic approach combining a Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to address the challenges of energy efficient and reliable node deployment. The GA PSO hybrid leverages GAs strong exploration capabilities and PSOs rapid convergence, achieving an optimum stability between coverage and energy consumption. The performance of the proposed approach is evaluated against GA and PSO alone and the innovatory meta heuristic based Competitive Multi Objective Marine Predators Algorithm (CMOMPA) across varying sensing ranges. Simulation results demonstrate that GA PSO requires 15% to 25% fewer sensor nodes and maintains 95% or more area coverage while maintaining the…
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