Minimizing a real-time task set through ...
Type de document :
Communication dans un congrès avec actes
DOI :
Titre :
Minimizing a real-time task set through Task Clustering
Auteur(s) :
Bertout, Antoine [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
LIFL - DART/Émeraude
Contributions of the Data parallelism to real time [DART]
Forget, Julien [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
LIFL - DART/Émeraude
Contributions of the Data parallelism to real time [DART]
Olejnik, Richard [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
LIFL - DART/Émeraude
Contributions of the Data parallelism to real time [DART]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
LIFL - DART/Émeraude
Contributions of the Data parallelism to real time [DART]
Forget, Julien [Auteur]

Laboratoire d'Informatique Fondamentale de Lille [LIFL]
LIFL - DART/Émeraude
Contributions of the Data parallelism to real time [DART]
Olejnik, Richard [Auteur]

Laboratoire d'Informatique Fondamentale de Lille [LIFL]
LIFL - DART/Émeraude
Contributions of the Data parallelism to real time [DART]
Titre de la manifestation scientifique :
Proceedings of the 22nd International Conference on Real-Time Networks and Systems
Ville :
Versailles
Pays :
France
Date de début de la manifestation scientifique :
2014-10-08
Date de publication :
2014-10-08
Mot(s)-clé(s) en anglais :
real-time scheduling task clustering functionality to task mapping
Discipline(s) HAL :
Informatique [cs]/Systèmes embarqués
Résumé en anglais : [en]
In the industry, real-time systems are specified as a set of hundreds of functionalities with timing constraints. Implementing those functionalities as threads in a one-to-one relation is not realistic due to the overhead ...
Lire la suite >In the industry, real-time systems are specified as a set of hundreds of functionalities with timing constraints. Implementing those functionalities as threads in a one-to-one relation is not realistic due to the overhead caused by the large number of threads. In this paper, we present task clustering, which aims at minimizing the number of threads while preserving the schedulability. We prove that our clustering problem is NP-Hard and describe a heuristic to tackle it. Our approach has been applied to fixed-task or fixed-job priority based scheduling policies as Deadline Monotonic (DM) or Earliest Deadline First (EDF).Lire moins >
Lire la suite >In the industry, real-time systems are specified as a set of hundreds of functionalities with timing constraints. Implementing those functionalities as threads in a one-to-one relation is not realistic due to the overhead caused by the large number of threads. In this paper, we present task clustering, which aims at minimizing the number of threads while preserving the schedulability. We prove that our clustering problem is NP-Hard and describe a heuristic to tackle it. Our approach has been applied to fixed-task or fixed-job priority based scheduling policies as Deadline Monotonic (DM) or Earliest Deadline First (EDF).Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :
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