Stochastic coverage analysis of Wireless Sensor Network with hybrid sensing model

In wireless sensor networks (WSNs), boolean sensing model are popularly adopted for coverage analysis since analytical and asymptotic analysis carried with this model are simple and tractable. As the boolean sensing model assumes, however, it is unlikely that sensing capability of sensor drop abruptly from perfect detection capability to zero. Hence, sensing capability characterization in such boolean model with two discrete states 1 and 0 conveying successful and failed detection probability respectively, is unrealistic. This implies that there might be a chance to detect an event occurring at distances greater than the boolean sensing radius. By ignoring this extra sensing capacity, the boolean model may not fully utilize the sensing capacity of the sensors which may results activation of more redundant sensor nodes thus increasing interferences and decreasing the life time of the sensor network. Being motivated with this well established fact, in this paper, coverage analysis for 2D- regular planar area is carried with hybrid sensing model which can account for additional exponentially decreased sensing capability beyond boolean sensing radius. This paper provides the minimum bound in the number of required sensor nodes to cover the monitoring interest area for guaranteeing certain coverage-threshold in stochastic sensing coverage field.