A Probabilistic Calculus for Probabilistic Real-Time Systems

Luca Santinelli 1 Liliana Cucu-Grosjean 2
2 AOSTE - Models and methods of analysis and optimization for systems with real-time and embedding constraints
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Paris-Rocquencourt, Laboratoire I3S - COMRED - COMmunications, Réseaux, systèmes Embarqués et Distribués
Abstract : Challenges within the real-time research are mostly in terms of modeling and analyzing the complexity of actual real-time embed- ded systems. Probabilities are effective in both modeling and analyzing embedded systems by increasing the amount of information for the description of elements composing the system. Elements are tasks and applications which need resources, schedulers which execute tasks, and resource provisioning which satisfy the resource demand. In this work we present a model which considers component-based real-time systems with component interfaces able to abstract both the functional and non-functional require- ments of components and the system. Our model faces probabilities and probabilistic real-time systems unifying in the same framework probabilistic scheduling techniques and compositional guarantees varying from soft to hard real-time. We provide an algebra to work with the probabilistic notation developed and develop analysis in terms of sufficient probabilistic schedulability conditions for task systems with either preemptive fixed-priority or earliest deadline first scheduling paradigms.
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Journal articles
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https://hal.inria.fr/hal-01244333
Contributor : Liliana Cucu-Grosjean <>
Submitted on : Tuesday, December 15, 2015 - 4:07:24 PM
Last modification on : Tuesday, March 26, 2019 - 2:28:03 PM

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Luca Santinelli, Liliana Cucu-Grosjean. A Probabilistic Calculus for Probabilistic Real-Time Systems. ACM Transactions on Embedded Computing Systems (TECS), ACM, 2015, RTAS2012 special issue, 14 (3), ⟨10.1145/2717113⟩. ⟨hal-01244333⟩

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