Volume 8 Issue 3 ( September 2021 )

Pages_601-609

Estimating the Coverage Performance of a Wireless Sensor Network Considering Boundary Effects in the Presence of Sensor Failure

Mini, Ashok Pal

[ABSTRACT ]

Coverage is one of the most critical performance metric of wireless sensor networks (WSNs) because it shows how well a region of interest (RoI) is being monitored by the deployed network. In general, the RoI is either circular or rectangular in shape which have boundary regions. Sensor nodes (SNs) deployed in these regions suffer boundary effects (BEs), i.e., the useful coverage area of an SN deployed near the boundary regions is less as compared to the SNs deployed in the middle of the RoI. It is imperative to consider these BEs while evaluating the performance of WSNs because analytical results derived for large networks are not valid for finite networks. In addition, SNs of a deployed WSN are prone to failure due to a large number of factors such as battery drainage, high temperature, and other environmental conditions. Earlier researchers have ignored the impact of BEs in the presence of sensor failure while evaluating the coverage performance of WSNs. In this work, we derive an analytical model by considering BEs and sensor failure to achieve a closed form expression for the k-coverage performance of a WSN deployed in a rectangular RoI. Further, we analyze the influence of various network parameters such as number of SNs, sensing range, and sensor failure rate on the k-coverage performance of the network. The results obtained using the proposed model show a good match with simulations outcomes with Root Mean Square Error (RMSE) no more than 0.03, thus, validating our model. For rs = 80 m and N = 100, 1-coverage probabilities are found to be 0.9874, 0.9313 and 0.8069 for k = 1, 2 and 3 respectively showing that the k-coverage probability deriorates with the increase in the value of k.

Keywords: wireless sensor networks; binary sensing model; k -coverage probability; sensor failure rate; boundary effects.