Role of Autonomy in a Distributed Sensor Network for Surveillance

This paper presents the results of endowing the social parameter, autonomy, on a distributed sensor network used for surveillance of multiple targets that crisscross a rectangular surveillance zone. Crossing targets are ascribed priorities by a priority ascription scheme based on fuzzy inference methods. The scheme fuses local and global priorities of a target through the parameter autonomy that has values in [ ] 1 , 0 . Sensors coordinate to allocate themselves to a particular target. Autonomy affects this process of allocation of sensors to targets. Lower autonomy biases allocation of sensors to targets that require short durations of tracking while higher autonomy biases allocation of sensors to targets that require longer tracking time. Test cases are presented regarding how changes in autonomy affect the tracking performance of the system. Conclusions are derived that suggest when high or low values of autonomy are beneficial to the system.