Coverage holes in Wireless Sensor Network (WSN) cause poor network performance and low network service quality. To solve these problems, a Coverage Hole Detection Algorithm based on Relative Position of Intersections (CHDARPI) was proposed. First, the hole boundary nodes were defined and Relative Position of Intersections (RPI) of the link between adjacent boundary nodes was calculated. Then, the starting node of hole detection was selected based on the policy of Number of Incomplete Coverage Intersections (NICI) priority, which guaranteed the concurrent detection of the connected coverage holes. Finally, in the process of coverage hole detection, the message of hole detection was limited within the hole boundary nodes, and the forwarding strategies under different scenarios were formulated according to the sizes of the direction angles of the forwarding nodes, which ensured the efficiency of coverage hole detection. The simulation results show that, compared with the existing Distributed Coverage Hole Detection algorithm (DCHD) and Distributed Least Polar Angle algorithm (DLPA), the proposed CHDARPI decreases the average detection time and detection energy consumption by at least 15.2% and 16.7%.

The limited resources of wireless sensor network nodes cause the poor completeness and timeliness of data collection. To solve these problems, a multi-objective path planning model for Mobile Charging Devices (MCD) jointing mobile charging and data collection was established, and a Path Planning algorithm based on Greedy Strategy for MCD jointing wireless charging and data collection (PPGS) was proposed. Firstly, the monitoring area was divided into many seamless regular hexagon cells, so as to effectively reduce the number of cells visited by MCD. Then, the parameters such as the node energy and the quantity of data collection were predicted by using the Markov model, and the anchor minimum stopping time and anchor maximum waiting time for MCD were predicted based on the above. Compared with the existing Delay-Constrained Mobile Energy Charging algorithm (DCMEC) and Mobile Device Scheduling Algorithm and Grid-Based Algorithm (GBA+MDSA), the proposed algorithm has lower complexity and does not need to know the actual location information of nodes and anchors in advance. The simulation results show that, the proposed PPGS can guarantee the completeness and timeliness of data collection with a small number of MCD in wireless sensor network.