Dynamic Clustering for Acoustic Target Tracking in Wireless Sensor Networks
Source: University of Illinois
In the paper, the authors devise and evaluate a fully decentralized, light-weight, dynamic clustering algorithm for target tracking. Instead of assuming the same role for all the sensors, they envision a hierarchical sensor network that is composed of a static backbone of sparsely placed high-capability sensors which will assume the role of a Cluster Head (CH) upon triggered by certain signal events; and moderately to densely populated low-end sensors whose function is to provide sensor information to CHs upon request. A cluster is formed and a CH becomes active, when the acoustic signal strength detected by the CH exceeds a pre-determined threshold.