Statistical Analysis and Energy-Efficient Routing for Tsunami Early Alarming in Internet of Underwater Things Using SDN Infrastructure

This paper presents a novel, energy-efficient routing approach for underwater sensor networks in tsunami early warning. Our system utilizes sensor nodes equipped with piezoelectric energy harvesting to extend network lifetime and stability. Continuous sensing is replaced with a duty-cycled approach to conserve energy, where the ocean surface is divided into regions and sensor nodes are grouped. These groups become active at designated intervals, while others remain dormant. The system leverages satellite networks to complement the underwater sensor network, enabling collected data to reach the central hub of early warning systems. A statistical analysis assigns scores to potential routes based on their energy consumption, prioritizing low-energy paths. Probability theory is employed to calculate the minimum number of transmission paths needed to achieve a predetermined level of reliability. A well-established tsunami wave prediction system is used to select the most suitable next hop for data transmission to avoid interference with tsunami wave propagation. Simulation results demonstrate significant improvements in energy efficiency, end-to-end delay, sensor and relay node lifespan, and network stability compared to recent research. These achievements highlight the effectiveness of our proposed routing approach in achieving energy efficiency and reliable data transmission within a tsunami early warning system.