Flexible support for time and costs in scenario-aware dataflow

Arnd Hartmanns, H. Hermanns, Michael Bungert

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 2 Citations

Abstract

Scenario-aware dataflow is a formalism to model modern dynamic embedded applications whose behaviour is heavily dependent on input data or the operational environment. Key behavioural aspects are the execution times and energy consumption of a system's components. In this paper, we introduce flexible scenario-aware dataflow: a proper generalisation of previous definitions that allows any execution time to be specified as discretely or continuously random or nondeterministic. Additionally, it supports the modelling of abstract costs like the energy usage of components. We give a formal compositional semantics in terms of networks of stochastic timed automata. We have implemented support for analysing performance properties of flexible scenario-aware dataflow graphs via simulation and model checking. A number of reduction techniques are applied to make the underlying state spaces tractable for model checking. We evaluate the scalability and performance of our new model and implementation on standard benchmarks.
LanguageUndefined
Title of host publicationProceedings of the 13th International Conference on Embedded Software (EMSOFT 2016)
Place of PublicationNew York
PublisherAssociation for Computing Machinery
Pages3
Number of pages10
ISBN (Print)978-1-4503-4485-2
DOIs
StatePublished - Oct 2016

Publication series

Name
PublisherACM

Keywords

  • EWI-27540
  • METIS-320923
  • IR-103038

Cite this

Hartmanns, A., Hermanns, H., & Bungert, M. (2016). Flexible support for time and costs in scenario-aware dataflow. In Proceedings of the 13th International Conference on Embedded Software (EMSOFT 2016) (pp. 3). New York: Association for Computing Machinery. DOI: 10.1145/2968478.2968496
Hartmanns, Arnd ; Hermanns, H. ; Bungert, Michael. / Flexible support for time and costs in scenario-aware dataflow. Proceedings of the 13th International Conference on Embedded Software (EMSOFT 2016). New York : Association for Computing Machinery, 2016. pp. 3
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Hartmanns, A, Hermanns, H & Bungert, M 2016, Flexible support for time and costs in scenario-aware dataflow. in Proceedings of the 13th International Conference on Embedded Software (EMSOFT 2016). Association for Computing Machinery, New York, pp. 3. DOI: 10.1145/2968478.2968496

Flexible support for time and costs in scenario-aware dataflow. / Hartmanns, Arnd; Hermanns, H.; Bungert, Michael.

Proceedings of the 13th International Conference on Embedded Software (EMSOFT 2016). New York : Association for Computing Machinery, 2016. p. 3.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Scenario-aware dataflow is a formalism to model modern dynamic embedded applications whose behaviour is heavily dependent on input data or the operational environment. Key behavioural aspects are the execution times and energy consumption of a system's components. In this paper, we introduce flexible scenario-aware dataflow: a proper generalisation of previous definitions that allows any execution time to be specified as discretely or continuously random or nondeterministic. Additionally, it supports the modelling of abstract costs like the energy usage of components. We give a formal compositional semantics in terms of networks of stochastic timed automata. We have implemented support for analysing performance properties of flexible scenario-aware dataflow graphs via simulation and model checking. A number of reduction techniques are applied to make the underlying state spaces tractable for model checking. We evaluate the scalability and performance of our new model and implementation on standard benchmarks.

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Hartmanns A, Hermanns H, Bungert M. Flexible support for time and costs in scenario-aware dataflow. In Proceedings of the 13th International Conference on Embedded Software (EMSOFT 2016). New York: Association for Computing Machinery. 2016. p. 3. Available from, DOI: 10.1145/2968478.2968496