A component-based framework for modeling and analyzing probabilistic real-time systems
Luca Santinelli, Patrick Meumeu Yomsi, Dorin Maxim, Liliana Cucu‐Grosjean · 2011
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.