Abstract
Data flow graphs are widely used for modeling and analysis of real-time streaming applications in which having a predictable and reliable implementation is an essential requirement. In this paper, we consider scheduling a set of data flow graphs such that liveness and boundedness properties are guaranteed, which leads to a predictable and correct behavior of the application. A formal translation method is proposed to map a given set of data flow graphs to a set of graph-based real-time tasks. Additionally, sufficient conditions are derived under which the obtained task set provides a semantically correct implementation of the given data flow graphs. It is shown that the proposed approach provides a higher level of design flexibility compared to the existing methods which use a simpler, i.e. periodic, task model.
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Notes
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Please notice that, \(p_i\) is an actor-specific parameter. However, for brevity reasons, it is not explicitly indicated in the notation.
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Mohaqeqi, M., Abdullah, J., Yi, W. (2016). Modeling and Analysis of Data Flow Graphs Using the Digraph Real-Time Task Model. In: Bertogna, M., Pinho, L., Quiñones, E. (eds) Reliable Software Technologies – Ada-Europe 2016. Ada-Europe 2016. Lecture Notes in Computer Science(), vol 9695. Springer, Cham. https://doi.org/10.1007/978-3-319-39083-3_2
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