Recently, there has been an increasing interest in monitoring and exploring underwater environments for scientific applications such as oceanographic data collection, marine surveillance, and pollution detection. Underwater acoustic sensor networks (UASNs) have been proposed as the enabling technology to observe, map, and explore the ocean. The unique characteristics of underwater aquatic environments such as low bandwidth, long propagation delays, and high energy consumption make the data forwarding process very difficult. Moreover, the mobility of the underwater sensors is considered an additional constraint for the success of the data forwarding process. That being said, most of the data forwarding protocols do not realistically consider the dynamic topology of underwater environment as sensor nodes move with the water currents, which is a natural phenomenon. In this research, we propose a mobility prediction optimal data forwarding (MPODF) protocol for UASNs based on mobility prediction. Indeed, by considering a realistic, physically inspired mobility model, our protocol succeeds to forward every generated data packet through one single best path without the need to exchange notification messages, thanks to the mobility prediction module. Simulation results show that our protocol achieves a high packet delivery ratio, high energy efficiency, and reduced end-to-end delay.
Energy-Efficient Mobility Prediction Routing Protocol for Freely Floating Underwater Acoustic Sensor Networks
