A Poisson-Disk Sampling Based Strategy for Node Placement in Wireless Sensor Network

Wireless Sensor Network (WSN) is a popular research field in recent years. This paper focuses on node placement of WSN applications, as monitoring physical value (e.g., temperature) or tracking paths of moving objects in surrounding environment. Inspired by anti-aliasing theory in sampling field, we present a Poisson-disk Sampling (PDS) based strategy for WSN node placement. With the theory of sampling, we study the spectral properties of node distribution, in order to reduce the deviation of data collection result. Simulation results show that PDS outperforms other placement methods, such as regular and random strategies, in terms of monitoring surrounding environment. In addition, we apply the PDS-based strategy to various WSN applications and design a simple energy-saving pattern with coverage and connectivity preserved.