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.