Adaptive energy-efficient and secure clustering-based routing architecture for underwater wireless sensor networks in marine environmental and ecosystem monitoring

Introduction Reliable long-term monitoring of coral reefs and other marine ecosystems is limited by the harsh underwater environment, restricted battery capacity of sensor nodes, and the high energy cost of acoustic communication. Underwater Wireless Sensor Networks (UWSNs) have emerged as a promising solution for marine environmental monitoring; however, challenges related to energy efficiency, secure communication, and reliable data collection remain significant. Methods This study proposes an integrated architecture for UWSNs that enhances energy efficiency, security, and data reliability. The framework combines a hybrid Adaptive Swarm Fitness Optimization–Golden Eagle Optimizer with K-Medoids clustering (ASFO–GEO–KM) for optimal cluster head selection, a Tiny Security (TinySec)-enabled Energy-aware Coral-Environmental Reliable Path (E-CERP) routing protocol, and Autonomous Underwater Vehicle (AUV)-assisted data collection. The ASFO–GEO–KM algorithm selects cluster heads based on residual energy, underwater link quality, and node density to improve load balancing and cluster stability. TinySec-enabled E-CERP provides authenticated, energy-aware multi-hop routing while accounting for underwater path loss and propagation delay. AUVs periodically collect aggregated data from cluster heads to reduce long-range acoustic transmissions and conserve node energy. Results Simulation results conducted in a realistic 3D marine environment demonstrate that the proposed framework outperforms existing approaches, including DEDG, AP, ALP, HECRA, GSA, and CTRGWO-CRP. The proposed system achieves a longer network lifetime, a higher packet delivery ratio, and significantly reduced routing overhead. Discussion By enabling secure, energy-efficient, and reliable underwater sensing, the proposed architecture supports long-term coral reef monitoring and marine ecosystem observation. It facilitates early detection of environmental stressors, such as thermal anomalies and turbidity spikes, thereby improving marine ecosystem protection and supporting conservation-oriented decision-making.