Schedulability analysis of dependent probabilistic real-time tasks - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2016

Schedulability analysis of dependent probabilistic real-time tasks

Résumé

The complexity of modern architectures has increased the timing variability of programs (or tasks). In this context, new approaches based on probabilistic methods are proposed to decrease the pessimism by associating probabilities to the worst case values of the programs (tasks) time execution. In this paper, we extend the original work of Chetto et al. [7] on precedence constrained tasks to the case of tasks with worst case execution times described by probability distributions. The precedence constraints between tasks are defined by acyclic directed graphs and these constraints are transformed in appropriate release times and deadlines. The new release times and deadlines are built using new maximum and minimum relations between pairs of probability distributions. We provide a probabilistic schedulability condition based on these new relations.
Fichier non déposé

Dates et versions

hal-01419741 , version 1 (19-12-2016)

Identifiants

Citer

Slim Ben-Amor, Dorin Maxim, Liliana Cucu-Grosjean. Schedulability analysis of dependent probabilistic real-time tasks. RTNS 2016 - 24th International Conference on Real-Time Networks and Systems, Oct 2016, Brest, France. pp.99-107, ⟨10.1145/2997465.2997499⟩. ⟨hal-01419741⟩
214 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More