Section: Research Program

Foundation

In order to check for the timing behavior and the reliability of distributed systems, TRIO team developed several techniques based on deterministic approaches ; in particular, we apply and extend analytical evaluation of worst case response times and when necessary, e.g. for large-scale communication systems as Internet based applications, we use techniques based on network calculus.

The arrival of complex hardware responding to the increasing demand for computing power in next generation systems exacerbates the limitations of the current worst-case real-time reasoning. Our solution to overcome these limitations is based on the fact that worst-case situations may have a extremely low probability of appearance within one hour of functioning (${10}^{-45}$ [7] ), compared to the certification requirements for instance (${10}^{-9}$ for the highest level of certification in avionics). Thus we model and analyze the real-time systems using probabilistic models and we propose results that are fundamental for the probabilistic worst-case reasoning over a given time window.

In the design of discrete event systems with hard real time constraints, the scheduling of the system’s activities is of crucial importance. This means that we have to devise scheduling policies that ensure the respect of time constraints on line and / or optimize the behavior of the system according to some other application-dependent performance criteria.

In order to foster the best quality for programs, their understanding has to be automated, or at made significantly easier. Thus, we focus on analyzing and modeling program code, program structure and program behavior, and presenting these pieces of information to the user (in our case, program designers and program developers). Modeling user interaction is to come as well.

In the design of embedded, autonomous systems, power and energy usage is of paramount importance. We thus strive to model energy usage, based on actual hardware, and derive context-aware optimizations to decrease peak power and overall energy usage.