Spatio-Temporal Correlation-Based Density Optimization in Wireless Underground Sensor Networks

This paper investigates the optimal sensor density in Wireless Underground Sensor Networks (WUSNs) to guarantee high monitoring accuracy with minimum deployment cost. In WUSNs, the density of underground sensors is expected to be as low as possible due to the high deployment cost. However, an extremely high density of underground sensors is required to maintain the full connectivity of WUSNs due to the harsh underground channel conditions. This conflict constitutes the greatest challenge to deploy the WUSNs and was not addressed before, to our knowledge. In this paper, a spatio-temporal correlation-based data collection scheme is proposed to release the unfeasible sensor density requirement of the full connectivity in WUSNs. More importantly, an explicit solution for sensor density optimization in WUSNs under the proposed data collection scheme is developed such that the effects of the dynamic underground channel conditions, the spatio- temporal correlations, the network connectivity, and the random or controlled mobility of mobile sinks are captured. The results of this paper provide principles and guidelines for the design and deployment of wireless underground sensor networks.