Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023)

Real-time embedded computing systems monitor and, often, control artifacts or other systems that interact with the physical world. Examples of such systems include avionics systems, automotive systems and medical robotics. Such real-time embedded systems are safety critical; their failure may result in harm to people or their environment.

The overarching theme of my proposed program is to avoid, or limit, failures of real-time embedded computing systems. Failures may be a result of:
* design and implementation failures (at both the hardware and software layers);
* operational hardware/component failures;
* resource allocation problems that manifest as timing errors when the system is not able to respond within timing bounds or deadlines.

I specifically intend to advance the state of the art in scheduling and timing-related problems as well as with detection, diagnosis and recovery from hardware component failures. I will also build upon work in approximate computing to make output quality tradeoffs when it is more critical to meet timing constraints.

My effort takes into consideration some of the different pressures that influence the development of real-time embedded systems such as the need for reduced size, weight and power consumption (sometimes called SWaP constraints) of the computing platforms. These pressures result in the colocation of computing activities of different criticalities on the same hardware platform (e.g., on a UAV, a task that takes photographs is less critical than the task that is responsible for aircraft stability). Such designs result in mixed-criticality systems . Nevertheless, safety critical systems need to meet the requirements highlighted in safety standards such as IEEE 26262. These standards enable safety certification, and they indicate the acceptable failure rates for tasks at different criticality levels.

Much of the recent work in the area of mixed-criticality real-time scheduling has focused on dual criticality systems. Tasks are either high or low criticality, and most existing work treats low criticality tasks as best-effort tasks. In other words, in prior work, researchers have ensured that high-criticality tasks meet their deadlines and low-criticality tasks are dropped even when this is not necessary. The approach taken in prior work does not also match with safety standards which indicate a failure probability or failure rate for each criticality level (so it is possible for a high-criticality task to fail, but not at the same rate as a low-criticality task).

Via this grant, I intend to develop tractable probabilistic analysis methods as well runtime support for real-time mixed-criticality systems . In the area of fault tolerance, there has been some work that examines mixed criticality systems, but more work is needed in terms of platforms and analysis methods to ensure compliance with safety standards and certification processes.