Coverage Maximization of Underwater WSN for Coral Reef Monitoring Using Heuristic Algorithms

Coral reefs support an extraordinary biodiversity, providing habitats for countless marine species and acting as natural barriers that protect coastal ecosystems. However, their location at the ocean floor makes monitoring and conservation challenging. The goal of UWSNs is to achieve maximum coverage of the coral reef area and ensure precise localization. Water currents, varying depths, and acoustic signal attenuation complicate data collection. Target distance, field of view, sensing distance, sensing angle affects the coverage. Optimizing these factors requires determining the best positions and orientations for sensors to cover the maximum reef area with minimal overlap or gaps. To address this, heuristic algorithms specifically, Ant Colony Optimization (ACO) and Emperor Penguin Algorithm (EPA), are combined to form a hybrid approach. Then it is applied to optimize sensor placement, iterating through configurations to maximize coverage. By simulating underwater environments and employing a hybrid heuristic algorithm, we can maximize coverage and enhance localization in UWSNs.