Received signal strength-based location verification technique in Wireless Sensor Network using Spline curve

Location verification is crucial in many Wireless Sensor Networks (WSNs) applications. To accurately identify a node’s position, location verification is required, eliminating the possibility of a wrong location due to multiple environmental factors. In the current study, we propose a novel pattern-matching approach for verifying sensors’ location having minor overhead (e.g., low power consumption and processing time) on the network while not using any additional hardware like GPS. The Spline curve, used for designing and controlling shapes in computer graphics, is used as the basis to verify the reported location of the sensor nodes of the network. A moving object surrounding an access point (AP) is introduced to incorporate the environmental obstruction, which obstructs Received Signal Strength Indicators from the nodes during communication with the AP. Several Cubic Bezier Curves are generated, taking RSSI from four nodes at a time, which later efficiently identifies any node’s location change along with the amount of difference. The algorithm is implemented in the Cooja simulator, which shows a satisfactory performance with location verification accuracy of up to 90%. The new parameter RSSI range factor (RRF) introduced in the proposed work estimates the amount of location change with an accuracy of up to 99%.