Phase optimization for control/fusion applications in dynamically composed sensor networks

The variable acquisition of distributed sensor perception promises an effective utilization of these data across different applications. Multiple observations enable an increase in the quality of the system output. However, the dynamic composition disables all off-line optimization approaches, especially for sensor-application-scheduling. This paper addresses the need for an online adjustment of periodically working sensors and fusion/control applications. Based on a number of common goals - e.g., minimization of the variance of sensor data or the age of data sets - we deduce different metrics. For one aspect, the number of input counts, we propose a mathematical description and apply related optimizations. We use an an example analysis to illustrate further research goals.