A Component-Based Framework for Modeling and Analyzing Probabilistic Real-Time Systems
Identifieur interne : 002193 ( Main/Merge ); précédent : 002192; suivant : 002194A Component-Based Framework for Modeling and Analyzing Probabilistic Real-Time Systems
Auteurs : Luca Santinelli [France] ; Patrick Meumeu Yomsi [France] ; Dorin Maxim [France] ; Liliana Cucu-Grosjean [France]Source :
Abstract
A challenging research issue of analyzing a real-time system is to model the tasks composing the system and the resource provided to the system. In this paper, we propose a probabilistic component-based model which abstracts in the interfaces both the functional and non-functional requirements of such systems. This approach allows designers to unify in the same framework probabilistic scheduling techniques and compositional guarantees that go from soft to hard real-time. We provide sufficient schedulability tests for task systems using such framework when the scheduler is either preemptive Fixed-Priority or Earliest Deadline First.
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<front><div type="abstract" xml:lang="en">A challenging research issue of analyzing a real-time system is to model the tasks composing the system and the resource provided to the system. In this paper, we propose a probabilistic component-based model which abstracts in the interfaces both the functional and non-functional requirements of such systems. This approach allows designers to unify in the same framework probabilistic scheduling techniques and compositional guarantees that go from soft to hard real-time. We provide sufficient schedulability tests for task systems using such framework when the scheduler is either preemptive Fixed-Priority or Earliest Deadline First.</div>
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