CostEfficient Node Deployment for Intrusion Detection in Underwater Sensor Networks Underwater sensor network has broad application prospects for performing underwater warning, target detection, and marine environment monitoring. However, traditional cubefilled fullcoverage node deployment schemes are costly and infeasible to detect target objects due to the considerably redundant nodes. In this paper, we propose a new scheme with a low cost to detect the target in dynamic waters to reduce the cost of the deployment. Our scheme controls the distributed sensors to move and construct an angular sensor barrier through which the target may pass. The profilebased barrier deployment scheme only needs to adjust node depth to reduce movement costs. During depth adjustment, the proposed method takes the node density, the residual energy of the node and the node movement effect into account so that the randomly distributed nodes are sunk at different depths, and the redundant nodes are removed by the 2Voronoi diagram lemma. We use the simulation experiment to evaluate the coverage and energy consumption during the movement of the nodes. The analysis of the experimental results shows that the method has good coverage performance. Also, it can reduce and balance energy consumption during the anchor node deployment to extend network uptime.

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.