Using fractal clustering to explore behavioral correlation
Fernando Rodrigues, Ângelo Brayner, José Everardo Bessa Maia · 2015
Sensor clustering is an efficient strategy to reduce the number of messages flowing in a Wireless Sensor Network (WSN) and thereby reducing the energy consumption. This paper presents a new approach to cluster sensors in WSNs, called Behavioral Correlation in WSN (BCWSN), which is based on the behavior of recent historical data collected by sensors. The proposed approach initializes clusters using the concepts of similarity in magnitude and trend of sensed data, and implements the notion of Fractal Clustering to dynamically find the best configuration for clusters. BCWSN can reduce the number of messages injected into the network when compared to approaches implementing temporal correlation, while RMSE remains roughly stable.