On Least Idle Slot First Co-scheduling of Update and Control Tasks in Real-Time Sensing and Control Systems

Typical real-time sensing and control systems consist of a set of update tasks for installing sensor measurements from the operation environment and a set of control tasks to access to these measurements for making control decisions. Although configuring the sensors with higher sampling rates could improve the accuracy of the measurements and control quality in general, scheduling high frequent update jobs may seriously affect the schedulability of the control tasks. Missing or delaying the control tasks may severely degrade the overall control performance of the system. In this paper, instead of using the traditional periodic update model, we adopt the a periodic update model in generating update jobs for maintaining data validity. We propose an adaptive co-scheduling algorithm called Least Idle Slot First (LISF) to schedule the update tasks and control tasks with the purposes to meet the deadlines of the control tasks and maximize the quality of control (QoC) offered by the control tasks. LISF schedules the jobs in the ascending order of the number of available idle slots before their deadlines and defers the release times of update jobs as long as the corresponding data objects are maintained within the required quality. The experiment results show that LISF can effectively improve the system schedulability and the control performance in the real-time sensing and control systems.