In recent years, there has been a great deal of interest in underwater sensor networks (UWSNs) because they can effectively monitor the submerged environment. However, due to the long delay, high bit error rate, and limited propagation bandwidth of underwater acoustic channels, the media access control (MAC) protocol cannot function effectively in underwater acoustic sensor networks, particularly in offshore waters. To solve these issues, an MAC protocol with time synchronization and power control (TSPC) is proposed for a particular scenario. In addition, the proposed protocol is a joint channel access scheme, and the central nodes are deployed on an offshore seabed, which can be used as a synchronization reference standard time. A power control strategy is also implemented to limit the communication range of nodes. In brief, integrating TSPC with layered concepts and distributed clustering algorithms can effectively prevent communication collisions and reduce the energy consumption of UWSNs. The simulation results indicate that the TSPC MAC protocol performs well with regard to packet transmission rate, synchronization error, collision-free operation, and energy consumption.

In recent years, Underwater Acoustic Sensor Networks (UASNs) have gained considerable attention for their unique role in detecting and monitoring the underwater environment. However, due to the long propagation time, high bit error rate, and limited bandwidth of underwater acoustic systems, the design of media access control (MAC) protocols is extremely complex, especially for the power consumption of UASNs. Therefore, this paper proposes an energy-efficient MAC protocol for three-dimensional UASNs with time synchronization and power control (TDTSPC-MAC). The proposed protocol is a hybrid access scheme for three-dimensional UASN using techniques such as time synchronization, power control, clustering, layering, and sleep mechanisms. Moreover, the TDTSPC-MAC protocol uses the hierarchical concept and distributed clustering algorithm to divide the three-dimensional space, and combines time synchronization and power control strategies to avoid collisions. Besides, energy consumption is reduced through monitoring and sleep mode. Simulation results demonstrate that the proposed TDTSPC-MAC protocol has reasonable data transmission delay time, throughput, energy consumption, and other performance.

With the wide application of Underwater Wireless Sensor Networks (UWSNs) in various fields, more and more attention has been paid to deploying and adjusting network nodes. A UWSN is composed of nodes with limited mobility. Drift movement leads to the network structure’s destruction, communication performance decline, and node life-shortening. Therefore, a Node Adjustment Scheme based on Motion Prediction (NAS-MP) is proposed, which integrates the layered model of the ocean current’s uneven depth, the layered ocean current prediction model based on convolutional neural network (CNN)–transformer, the node trajectory prediction model, and the periodic depth adjustment model based on the Seagull Optimization Algorithm (SOA), to improve the network coverage and connectivity. Firstly, the error threshold of the current velocity and direction in the layer was introduced to divide the depth levels, and the regional current data model was constructed according to the measured data. Secondly, the CNN–transformer hybrid network was used to predict stratified ocean currents. Then, the prediction data of layered ocean currents was applied to the nodes’ drift model, and the nodes’ motion trajectory prediction was obtained. Finally, based on the trajectory prediction of nodes, the SOA obtained the optimal depth of nodes to optimize the coverage and connectivity of the UWSN. Experimental simulation results show that the performance of the proposed scheme is superior.