The underwater wireless sensor network is an important component of the underwater three-dimensional monitoring system. Due to the high bit error rate, high delay, low bandwidth, limited energy, and high dynamic of underwater networks, it is very difficult to realize efficient and reliable data transmission. Therefore, this paper posits that it is not enough to design the routing algorithm only from the perspective of the transmission environment; the comprehensive design of the data transmission algorithm should also be combined with the application. An edge prediction-based adaptive data transmission algorithm (EP-ADTA) is proposed that can dynamically adapt to the needs of underwater monitoring applications and the changes in the transmission environment. EP-ADTA uses the end-edge-cloud architecture to define the underwater wireless sensor networks. The algorithm uses communication nodes as the agents, realizes the monitoring data prediction and compression according to the edge prediction, dynamically selects the transmission route, and controls the data transmission accuracy based on reinforcement learning. The simulation results show that EP-ADTA can meet the accuracy requirements of underwater monitoring applications, dynamically adapt to the changes in the transmission environment, and ensure efficient and reliable data transmission in underwater wireless sensor networks.
Keywords: auto regressive and moving average (ARMA); edge computing; intelligent routing algorithm; reinforcement learning (RL); underwater monitoring applications; underwater wireless sensor networks (UWSNs).