Analysis of Embedded Controllers Subject to Computational Overruns

Microcontrollers have become an integral part of modern everyday embedded systems, such as smart bikes, cars, and drones. Typically, microcontrollers operate under real-time constraints, which require the timely execution of programs on the resource-constrained hardware. As embedded systems are becoming increasingly more complex, microcontrollers run the risk of violating their timing constraints, i.e., overrunning the program deadlines. Breaking these constraints can cause severe damage to both the embedded system and the humans interacting with the device. Therefore, it is crucial to analyse embedded systems properly to ensure that they do not pose any significant danger if the microcontroller overruns a few deadlines.However, there are very few tools available for assessing the safety and performance of embedded control systems when considering the implementation of the microcontroller. This thesis aims to fill this gap in the literature by presenting five papers on the analysis of embedded controllers subject to computational overruns. Details about the real-time operating system's implementation are included into the analysis, such as what happens to the controller's internal state representation when the timing constraints are violated. The contribution includes theoretical and computational tools for analysing the embedded system's stability, performance, and real-time properties.The embedded controller is analysed under three different types of timing violations: blackout events (when no control computation is completed during long periods), weakly-hard constraints (when the number of deadline overruns is constrained over a window), and stochastic overruns (when violations of timing constraints are governed by a probabilistic process). These scenarios are combined with different implementation policies to reduce the gap between the analysis and its practical applicability. The analyses are further validated with a comprehensive experimental campaign performed on both a set of physical processes and multiple simulations.In conclusion, the findings of this thesis reveal that the effect deadline overruns have on the embedded system heavily depends the implementation details and the system's dynamics. Additionally, the stability analysis of embedded controllers subject to deadline overruns is typically conservative, implying that additional insights can be gained by also analysing the system's performance

Scheduling Tasks with Markov-Chain Based Constraints

Markov-Chain (MC) based constraints have been shown to be an effective QoS measure for a class of real-time systems, particularly those arising from control applications. Scheduling tasks with MC constraints introduces new challenges because these constraints require not only specific task finishing patterns but also certain task completion probability. Multiple tasks with different MC constraints competing for the same resource further complicates the problem. In this paper, we study the problem of scheduling multiple tasks with different MC constraints. We present two scheduling approaches which (i) lead to improvements in “overall ” system performance, and (ii) allow the system to achieve graceful degradation as system load increases. The two scheduling approaches differ in their complexities and performances. We have implemented our scheduling algorithms in the QNX real-time operating system environment and used the setup for several realistic control tasks. Data collected from the experiments as well as simulation all show that our new scheduling algorithms outperform algorithms designed for window-based constraints as well as previous algorithms designed for handling MC constraints.