Square region-based coverage and connectivity probability model in wireless sensor networks

Sensing coverage and network connectivity are two fundamental issues in wireless sensor networks (WSNs). Due to resource constraints of sensor nodes, it may not be possible, or necessary, to provide full coverage and/or connectivity in WSNs. Under a certain coverage and connectivity requirement, the node deployment strategy becomes a challenging issue in randomly deployed networks. In this paper, we propose a square region-based coverage and connectivity probability model (SCCP), which reflects the relations among the coverage and connectivity rates, the number of sensor nodes, the sensing and communication ranges of sensor nodes, and the network size. This model can calculate the number of sensor nodes that need to be deployed for maintaining a certain coverage and/or connectivity rate. The simulation results have shown that the error-rate of node deployment is less than 5%, which is defined as the absolute difference between the number of sensor nodes obtained from the theoretical analysis and the number obtained from the simulation, divided by the number of sensor nodes obtained from the theoretical analysis. The proposed model is very useful in estimating the monitoring coverage and connectivity capacity when sensor nodes are distributed randomly and uniformly.