Node Deployment Technique in Underwater Wireless Sensor Networks (UWSNs) for Energy and Coverage Optimization Using a Hybrid Fruit Fly and Bat Algorithms (FOA‐BOA)

Wireless sensor communication is a crucial technology nowadays; wireless sensor technology is not used only in terrestrial but also in underwater. Coverage and energy consumption are crucial challenges in underwater wireless sensor networks (UWSNs) due to the complexities of the aquatic environment and network connection costs. This study presents a hybrid fruit fly–bat optimization algorithm (FOA‐BOA) for sensor node deployment in UWSNs. The technique combines both fixed and mobile sensor nodes to improve network connectivity and coverage rate. A novel multi‐objective fitness function has been used for the optimization of coverage rate, connection cost, and network lifetime. It is used to optimize sensor node placement through modified bat and fruit fly optimization algorithms. Probability detection and a hybrid FOA‐BOA‐based multipoint search determine the optimal node deployment configuration. The hybrid FOA‐BOA achieves an impressive coverage rate of 96.9%, far surpassing the whale optimization search (WOS) (74.4%) and moth flame optimization (MFO) (78.8%). Simulation results conducted in MATLAB reveal that the proposed hybrid algorithm significantly enhances network coverage, reduces energy consumption, and extends the network lifetime in comparison to two existing algorithms.