Minimizing a real-time task set through ...
Document type :
Communication dans un congrès avec actes
DOI :
Title :
Minimizing a real-time task set through Task Clustering
Author(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]
Conference title :
Proceedings of the 22nd International Conference on Real-Time Networks and Systems
City :
Versailles
Country :
France
Start date of the conference :
2014-10-08
Publication date :
2014-10-08
English keyword(s) :
real-time scheduling task clustering functionality to task mapping
HAL domain(s) :
Informatique [cs]/Systèmes embarqués
English abstract : [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 ...
Show more >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).Show less >
Show more >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).Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
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