Probabilistic Modelling and Evaluation of Soft Real-Time Embedded Systems
Soft real-time systems are often analysed using hard real-time techniques, which are not suitable to take into account the deadline misses rate allowed in such systems. Therefore, the resulting system is over-dimensioned, thus expensive. To appropriately dimension soft real-time systems, adequate models, capturing their varying runtime behaviour, are needed. By using the concepts of a mathematically defined language, we provide a modelling approach based on patterns that are able to express the variations appearing in the system timing behaviour. Based on these modelling patterns, models can be easily created and are amenable to average case performance evaluation. By the means of a case study, we show the type of results that can be obtained from such an evaluation and how these results are used to dimension the system.
KeywordsModelling Pattern Design Space Exploration Kahn Process Network Average Case Performance Modular Performance Analysis
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