A data flow model with frequency arithmetic

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Abstract

Data flow formalisms are commonly used to model systems in order to solve problems of buffer sizing and task scheduling. A prerequisite for static analysis of a modeled system is the existence of a periodic schedule in which the sizes of communication channels can be bounded for an unbounded execution (consistency), and that communication dependencies do not introduce a deadlock in such an execution (liveness). In the context of Cyber-Physical Systems, components are often interfaced with the physical world and have frequency constraints. The existing data flow formalisms lack expressiveness to fully cover the expected behavior of these components. We propose an extension to Synchronous Data Flow (SDF) formalism, called Polygraph, that includes frequency constraints and adjustable communication rates. We show that with these extensions, the conditions for a model to be consistent and live are no longer sufficient, and we extend the corresponding theorems with necessary and sufficient conditions to preserve these properties. We also introduce a framework to check the liveness of a Polygraph model, implemented in the tool DIVERSITY, along with preliminary experiments to validate this approach.

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Dubrulle, P., Gaston, C., Kosmatov, N., Lapitre, A., & Louise, S. (2019). A data flow model with frequency arithmetic. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11424 LNCS, pp. 369–385). Springer Verlag. https://doi.org/10.1007/978-3-030-16722-6_22

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