Ensuring data freshness for periodic real-time tasks

Abstract : Automotive systems are composed of embedded applications which are continuously exchanging real-time data. Exchanged data are then propagated within a list of applications involved at different rates in the definition of a function. Different rates of executions for the applications provoke over-and/or under-sampling of data and the age of the data has an obvious impact on the driving decisions. Ensuring that the appropriate data are consumed by an application motivates to maintain the freshness or the temporal validity of real-time data. In this paper we propose a method calculating the freshness of the data for real-time systems where multi-rate sampling of data is considered.
Type de document :
Communication dans un congrès
the 12th Junior Researcher Workshop on Real-Time Computing, 2018, Poitiers, France. 2018, 〈https://rtns2018.ensma.fr/workshop.html〉
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https://hal.inria.fr/hal-01900328
Contributeur : Evariste Ntaryamira <>
Soumis le : dimanche 21 octobre 2018 - 21:29:36
Dernière modification le : vendredi 14 décembre 2018 - 17:35:41
Document(s) archivé(s) le : mardi 22 janvier 2019 - 13:11:48

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  • HAL Id : hal-01900328, version 1

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Evariste Ntaryamira, Cristian Maxim, Liliana Cucu-Grosjean. Ensuring data freshness for periodic real-time tasks. the 12th Junior Researcher Workshop on Real-Time Computing, 2018, Poitiers, France. 2018, 〈https://rtns2018.ensma.fr/workshop.html〉. 〈hal-01900328〉

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