Meta-Heuristic Solution for Route Optimization in Underwater Wireless Sensor Networks for Marine Applications

This research presents a novel approach to routing protocols within Marine Underwater Sensor Networks (M-USN) by integrating a Grey Wolf Optimization (GWO) strategy, designed to tackle the distinct challenges associated with subaquatic communications. Driven by the imperative to establish energy-efficient pathways for data transmission that enhance network longevity and conserve resources amidst the complex underwater milieu, the methodology draws inspiration from the hierarchical structuring observed in grey wolf packs to refine routing processes. By accommodating the fluctuating underwater dynamics, including changes in salinity levels, pressures, and visibility, the GWO-based method markedly augments cluster head selection efficiency, leading to a significant reduction in energy expenditures and bolstered data integrity. Comparative analysis through NS-2 simulator trials showcases the superior performance of the GWO protocol in comparison with established counterparts such as the Energy Efficient Routing Protocol, Directional Flooding based Routing, and the Hop-by-Hop Dynamic Addressing Based Routing, evidencing pronounced enhancements in the sustainability and operational efficiency of Underwater Wireless Sensor Networks (UWSNs). The investigation illuminates the feasibility of leveraging bio-inspired algorithms for the advancement of underwater communication systems, particularly in enhancing the efficacy of data transfer in subsea environments, with direct applicability to deep-sea exploration, conservation of marine life, and the guidance of unmanned subaquatic vehicles. The novelty of this work is attributed to its application of biological optimization mechanisms to the realm of underwater sensor networks, proposing a pioneering solution to the persistent obstacles faced in subsea data dissemination.