AEUSNF: Adaptive Energy-Efficient Underwater Sensor Network Framework

This study presents the Adaptive Energy-Efficient Underwater Sensor Network Framework (AEUSNF), an innovative approach aimed at enhancing the energy efficiency, data reliability, and operational lifespan of Underwater Wireless Sensor Networks (UWSNs). AEUSNF integrates advanced optimization techniques, including the Dragonfly Optimization Algorithm (DFO), adaptive communication strategies, dynamic energy profiling, fault tolerance mechanisms, and energy harvesting technologies. These components collectively tackle critical challenges such as high energy consumption, communication delays, limited node longevity, and network reliability issues. The framework employs hierarchical clustering to optimize node placement and utilizes real-time energy heatmaps to direct sink mobility, alongside adaptive power control to manage energy consumption effectively. To maintain uninterrupted connectivity, AEUSNF incorporates fault-tolerant solutions like redundancy and dynamic rerouting. Furthermore, energy harvesting modules harness underwater currents and thermal gradients, significantly prolonging network operation. Enhanced communication protocols, featuring data compression and dynamic duty cycling, reduce energy usage while ensuring reliable data transmission. AEUSNF continuously monitors and adjusts key performance metrics, enabling it to adapt dynamically to evolving underwater conditions. By addressing these critical challenges, AEUSNF provides a comprehensive and adaptable solution that substantially improves the efficiency, sustainability, and reliability of underwater sensor networks.