<![CDATA[Wireless Sensor Networks (WSNs) are widely deployed for large-scale environmental monitoring applications, particularly in remote and maritime areas where manual surveillance is costly and impractical. One of the major challenges in WSN deployment is achieving full sensing coverage and network connectivity while minimizing energy consumption and deployment density. This paper proposes an energy-aware multi-objective deployment optimization model based on Direct Radio Graph Medium (DRGM) modeling. The deployment problem is formulated as a multi-objective optimization task aiming to minimize the number of active sensor nodes while maintaining communication connectivity under predefined sensing and transmission constraints. A genetic algorithm–based optimization mechanism is employed to generate Pareto-optimal deployment solutions. The proposed model is evaluated using NS-2 simulations under various node densities and traffic rates. Simulation results show that the DRGM-based deployment achieves full coverage using only 10 sensor nodes, compared to 50–100 nodes in random deployment, corresponding to a node reduction of up to 90%. Furthermore, the proposed approach significantly reduces network power consumption and radio duty cycles, demonstrating its effectiveness for energy-efficient and scalable WSN deployment in large monitoring areas.]]>
Copyrights © 2026
