An eigenvector centrality-based mobile target tracking algorithm for wireless sensor networks

Abstract

We propose an eigenvector centrality (EVC)-based tracking algorithm to trace the trajectory of a mobile radioactive dispersal device (RDD) in a wireless sensor network. We propose that the sensor nodes simply sum up the strengths of the signals sensed in the neighbourhood over a sampling time period and forward the sum of the signals to a control centre (called sink). For every sampling time period, the sink constructs an adjacency matrix in which the entry for edge (i, j) is the sum of the signal strengths reported by sensor nodes i and j. The sink uses this adjacency matrix as the basis to determine the eigenvector centralities and uses the arithmetic mean (calculated by the sink) of the X and Y coordinates of the suspect sensor nodes (those having larger EVC) to predict the location of the RDD at a time instant corresponding to the middle of the sampling time period.