Probability-Based Coverage Algorithm for 3D Wireless Sensor Networks

We propose a probability-based K-coverage control approach (PKCCA) for the contradiction between the inherent uncertainty and strong fault-tolerance ability and robustness of wireless sensor networks in the monitoring of three-dimensional space. The entire monitoring region is to be covered by at least K sensors with probability T. A grid distribution and greedy heuristic are introduced to determine the best placement of sensors. Our approach will be terminated when a preset upper limit on the number of sensors is reached, or the coverage task is completed. We implement our approach and compare it against traditional random and uniform deployment. The results show that PKCCA uses less sensors to complete the same coverage task or same sensors to reach higher coverage degree. We also analyze the cases of preferential coverage for subregions. PKCCA is a better solution with high reliability and robustness to detect special environment with weak propagation of signal.