Lead-Uwsn: Adaptive Hybrid Lion Dolphin Algorithm for Dynamic Packet Delivery in UWSN

Underwater wireless sensor networks (UWSN) are viewed as promising technologies to gather meaningful data from underwater areas, especially to support environmental forecasting and military functions. The challenges presented in UWSNs with respect to the reliability and efficiency of underwater sensor nodes are a major concern for packet delivery in the network path. To address these issues, a new LEAD-UWSN technique is proposed in this work. The proposed LEAD-UWSN hybridizes the Lion Optimization Algorithm (LOA) and Dolphin Echolocation Algorithm (DEA) to reduce the issues encountered in underwater settings, such as packet losses, power consumption, and network delays. The proposed work LEAD-UWSN also improves the accuracy and efficiency of packet transmission over UWSN by integrating these LOA and DEA algorithms. The proposed technique was tested using MATLAB. The performance of LEAD-UWSN was evaluated in terms of end-to-end delay, packet delivery, energy consumption, and throughput. The results show that the proposed method has high efficiency and high reliability in comparison with performance metrics. The proposed method achieves a 6.59% accuracy in packet delivery with respect to transmission.