No abstract

No abstract

Providing guarantees on the system behavior is mandatory in order to let the robots enter our everyday life. Among these guarantees, proving the fulfillment of real-time constraints on the software is a key issue, as their violation could result into unexpected and unsafe behaviors. In this paper, we present a methodology to guarantee real-time constraints on component-based software architectures of robots. This methodology relies on the MAUVE language to model the component architecture, and on a set of analysis tools that first estimate the worst case execution time of elementary functions from actual component traces, and then check the real-time constraints of each component. We illustrate this process on the architecture developed for the autonomous navigation of a partially known area by a mobile robot. • We use a more detailed model of the task behavior; for that purpose, we rely on component-based models using the MAUVE language [11], and on a schedulability analysis that takes such models into account [12]. • We estimate WCET of tasks from actual measurements, then taking into account potential influence from input data and system interactions.

No abstract

Current processors have gone through multiple internal optimization to speed-up the average execution time e.g. pipelines, branch prediction. Besides, internal communication mechanisms and shared resources like caches or buses have a significant impact on Worst-Case Execution Times (WCETs). Having an accurate estimate of a WCET is now a challenge. Probabilistic approaches provide a viable alternative to single WCET estimation. They consider WCET as a probabilistic distribution associated to uncertainty or risk. In this paper, we present synthetic benchmarks and associated analysis for several LEON3 configurations on FPGA targets. Benchmarking exposes key parameters to execution time variability allowing for accurate probabilistic modeling of system dynamics. We analyze the impact of architecturelevel configurations on average and worst-case behaviors.