Cluster subdivision towards power savings for randomly deployed WSNs — An analysis using 2-D spatial poisson process
Dajin Wang · 2016
We propose to use a 2-dimensional (2-D for short) spatial Poisson process to model a WSN with randomly deployed sensors, and use the model to analyze a scheme that subdivides the clusters of a WSN to achieve an overall power savings. We assume no knowledge of how the sensors are spread in the sensing area, and hence need a statistical process to describe the distribution of all sensors. Assuming the 2-D spatial Poisson distribution, a comprehensive analysis is performed to estimate the power savings brought about by the proposed subdivision. Using hexagon as the shape of the cluster, the analysis shows that the subdivision scheme can yield significant savings in overall power consumption of sensors in the cluster.