A heuristic to minimize the cardinality of a real-time task set by automated task clustering

Antoine Bertout 1, 2, 3 Julien Forget 1, 2, 3 Richard Olejnik 1, 2, 3
1 DART - Contributions of the Data parallelism to real time
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe
2 LIFL - DART/Émeraude
LIFL - Laboratoire d'Informatique Fondamentale de Lille
Abstract : We propose in this paper a method to automatically map functionalities (blocks of code corresponding to high-level features) with real-time constraints to tasks (or threads). We aim at reducing the number of tasks functions are mapped to, while preserving the schedulability of the initial system. We consider independent tasks running on a single processor. Our approach has been applied with fixed-task or fixed-job priorities assigned in a Deadline Monotonic (DM) or a Earliest Deadline First (EDF) manner.
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Antoine Bertout, Julien Forget, Richard Olejnik. A heuristic to minimize the cardinality of a real-time task set by automated task clustering. Proceedings of the 29th Annual ACM Symposium on Applied Computing (SAC 2014), Apr 2014, Gyeongju, South Korea. ⟨10.1145/2554850.2554958⟩. ⟨hal-01016182⟩

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