Path Planning Method Based on the Location Uncertainty of Water Surface Nodes in Underwater Sensor Network The Underwater Sensor Network (USN) has great advantages in marine environmental monitoring. When collecting the perception information of sensor nodes, the mobile node can effectively compensate for the shortcomings of traditional multihop transmission modes. However, the complex marine environment causes the location uncertainty of nodes. Therefore, a path planning method based on the location uncertainty of water surface nodes in USN is proposed in this paper. Firstly, the structure of the USN based on the mooring model is introduced and the problem model of path planning is proposed. Secondly, the inevitable communication circle is obtained by analyzing the deviation range and communication range of water surface nodes. Thirdly, Convex Hull algorithm is used to plan the path in accordance with the inevitable communication circle of water surface nodes. Finally, simulation results show that the proposed method can obtain a shorter path under the premise of ensuring the completion of information collection.

A Subregional MonitoringOriented Topology Control Strategy in UWSNs Underwater wireless sensor networks (UWSNs) have become crucial for many different applications, such as marine pastures, which needs stratified aquaculture according to the habitat and range of activities of marine organisms. This type of application poses a significant challenge to network topology because strengthening the monitoring of the living conditions and collecting underwater data on organisms in different regions is necessary. In this paper, a new concept of subregional monitoring is proposed, and subregions with frequent activities of marine organisms are taken as the key monitoring areas, i.e., the areas of interest (AOIs). Then, SFRG, an energybalanced and robust topology based on scalefree network and rigid graph theory, is proposed to strengthen the monitoring of the AOIs. The topology of a rigid graph is constructed in AOI, and the entire network is scalefree network with powerlaw degree distribution, when the rigid graph is regarded as a node. Furthermore, a transmission algorithm based on the SFRG is suggested to prolong the network lifetime. The algorithm guarantees that 90% of the received packets are from the AOIs. The simulation results demonstrate that the SFRG effectively prolongs the network lifetime and improves the network robustness, which provides a strong support in strengthening the monitoring of AOIs and balancing the energy consumption.