A Method for Improving Delay-Sensitive Accuracy in Real-Time Embedded Systems

Timeliness and accuracy are two major concerns in many real-time embedded systems working in dynamic environments. It has been emphasized in the literature that in various real-time applications such as control systems and Kalman filters, delay is one main source of inaccuracy in the system. In this paper, we present a solution based on scheduling algorithms for the problem of inaccuracy in such systems. To this aim, first an accuracy model is introduced for systems which their accuracy is influenced by sampling and I/O delays. Then an algorithm called adjacency trade is presented to improve system accuracy while maintaining its timeliness. This algorithm follows an iterative approach and can be applied to each priority-based scheduling algorithm with no intervention in respecting the deadlines. Finally, through various simulation experiments, the effectiveness of this algorithm is examined against some algorithms in the literature.