Abstract
In this paper, we consider the problem of sensor resource management in decentralized tracking systems with
asynchronous communication and sensor selection. Due to the availability of cheap sensors, it is possible to
deploy a large number of sensors and use them to monitor a large surveillance region. Even though a large
number of sensors are available, due to frequency, power and other physical limitations, only a maximum of
certain number of sensors can be used by any fusion center at any one time. The problem is then to select the
sensor subsets that should be used at each sampling time in order to optimize the tracking performance under
the given constraints. In recent papers, we proposed algorithms to handle the above problem in centralized,
distributed and decentralized architectures. However, in the paper for sensor subset selection for decentralized
architecture, we assumed that all the fusion centers change their sensors at the same time, and their sensor
change time interval is fixed and known. However, in general case, fusion centers may change their sensors at
different time, and their sensor change intervals may not be fixed. In this case, the sensor management become
more difficult. We have to decide when to change the subsets, and how to incorporate the changes made in the
neighboring fusion centers in selecting the future sensor subsets. We propose an efficient algorithm to handle the
above problem in real time. Simulation results illustrating the performance of the proposed algorithm are also
presented.
