3D Dynamic Topology with Energy-Aware Forwarding in Underwater Acoustic Networks (MAEARS)

Dynamic topology, high latency, and restricted bandwidth are among the challenges of 3D underwater Acoustic Networks for offshore exploration, pollution monitoring, and oceanographic data collection. The proposed mobility adaptive paradigm addresses these issues for three-dimensional and natural harsh underwater environments without assumptions by integrated energy efficiency, mobility adaptation, and energy-aware forwarder node selection to extend network life. The proposed framework and algorithms dynamically adjust network structure and topology for node placement with their power level adjustments in real time. A modified random walk model for node mobility is incorporated to replicate realistic underwater movements. The energy consumption model considers duty cycle, inactivity, gearbox, reception, and sleep. Relay nodes are selected based on signal quality, residual energy, and proximity of available sink nodes to improve network coverage and load balancing. Mobility adaptive protocol is compared with existing established EECRP, the results demonstrated the increasing energy depletion throughout simulations in a steady manner and hence showed that MAEARS is energy efficient, allowing all nodes to stay operational. The protocol was performed with a throughput of 90.82 kbps and a PDR of 90.62% to 96.81%. selected relay nodes for forwarding packets well, relayed 3762 to 39392 packets, minimizing packet failures from 423 to 1411. It dramatically improves 3D UWSN performance and sustainability; adaptive energy-aware relay node selection guarantees reliable data transfer and network lifespan in harsh, dynamic underwater environments. MAEARS outperforms the current energy-efficient methods, PDR, and throughput. Practical implementations using machine learning to strengthen underwater sensor networks will be studied.