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Ahstract-A notion of interfaces based on regular languagesfor modelling and verification of real-time scheduling constraints was proposed in [5]. This initial notion considers task sets running on single resources, and simple deadline requirements. We extend the approach to enable support for complex task models running on systems with multiple resources. We show that this extension preserves all properties of the original notion. In addition, this extension gives rise to the application of our interfaces in the design of more complex systems, where components can be spread over distributed architectures.The work is complemented by an initial implementation that performs scheduling analysis for a relevant class of real-time interfaces. It actually constructs an interface for a system model if it satisfies a set of given real-time requirements.

Since the software part in today's designs is increasingly important, the impact of platform decisions with respect to the hardware and the software infrastructure (OS, scheduler, priorities, mapping) has to be explored in early design phases.In this paper, we present an extension of the existing SystemC TM -based OSSS design flow regarding software multi-tasking in system models. The simulation of the OSSS software run-time model supports different scheduling policies, as well as efficient timing annotations, and deadlines. Inter-task communication is modelled via userdefined Shared Objects. The impact of timing annotation granularity on the achievable simulation performance is studied. As a result, a lazy synchronisation scheme is proposed, that is based on omitting SystemC time synchronisations, that do not have observable effects on the application model.

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In this paper the modelling of a physical control system with SystemC AMS is described. The presented example, a crane controller, is compared with a Matlab/Simulink model in terms of simulation performance and accuracy. Due to numerical stability issues of the canonical implementation of the physical model, an external solver is integrated into the simulation.