A Model-Based Framework for the Specification and Analysis of Hierarchical Scheduling Systems

International audienceFor decades, schedulability analysis of Cyber-Physical Systems (CPS) has been conducted by analytical methods rather than model-based methods. However, CPS are getting more and more complicated, beyond the capability of analytical methods, as more sophisticated scheduling mechanisms are used. This encourages the use of model-based and automated verification techniques. These techniques must be flexible enough to be adapted to any system, and easy to use by system designers, without deep knowledge of formal verification. In this paper, we present a flexible model-based framework for specifying hierarchical scheduling systems and performing automated formal verification. It allows to easily specify complex scheduling mechanisms, with hierarchical scheduling units that can be analyzed efficiently in a compositional manner. Formal verification using statistical techniques is performed automatically by generating on-the-fly the formal models. Finally, the framework returns comprehensible feedback from the results of formal verification in the design tool

Compositional Predictability Analysis of Mixed Critical Real Time Systems

This paper introduces a compositional framework for analyzing the predictability of component-based embedded real-time systems. The framework utilizes automated analysis of tasks and communication architdepicts the structureectures to provide insight on the schedulability and data flow. The communicating tasks are gathered within components, making the system architecture hierarchical. The system model is given by a set of Parameterized Stopwatch Automata modeling the behavior and dependency of tasks, while we use Uppaal to analyze the predictability. Thanks to the Uppaal language, our model-based framework allows expressive modeling of the behavior. Moreover, our reconfigurable framework is customizable and scalable due to the compositional analysis. The analysis time and cost benefits of our framework are discussed through an avionic case study

Extending UPPAAL for the Modeling and Verification of Dynamic Real-Time Systems

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Contribution of ion emission to sputtering of uranium dioxide by highly charged ions

Measurements of the cluster size (n) distribution of secondary (UO$_{x})^{+}_{n}$ ions from sputtering of uranium dioxide (UO$_{2})$ by Ne8+, Ar8+ and Xe$^{q+}$ ions (q=10, 23) at fixed kinetic energy (81 keV) have been performed with a time-of-flight mass spectrometer. The cluster ion yields Y follow a power law $Y(n)\sim n^{\delta}$ with $-2.1<\delta <-1.5$. This is in contrast to a statistical recombination of the constituents upon ejection, but in agreement with the predictions of collective ejection models. Such a power law was also observed in the electronic stopping regime with MeV/u ions. The exponent $\delta$ is found to decrease with increasing projectile mass (and thus total sputter yield) at fixed kinetic energy. The ratio of emitted ionic clusters to monomers varies from 3 to 4.5 depending on the projectile. The contribution of positive ions to the total sputtering yield amounts to about 0.03%

A Framework for Evaluating Schedulability Analysis Tools

International audienceThere exists a large variety of schedulability analysis tools based on dierent, often incomparable timing models. This variety makes it dicult to choose the best t for analyzing a given real-time system. To help the research community to better evaluate analysis tools and their underlying methods, we are developing a framework which consists of (1) a simple language called RTSpec for specifying real-time systems, (2) a tool chain which translates a system specication in RTSpec into an input for various analysis tools, and (3) a set of benchmarks. Our goal is to enable users and developers of schedulability analysis tools to compare such tools systematically, automatically and rigorously