Minimizing the cardinality of a real-time task set by automated task clustering

Antoine Bertout; Julien Forget; Richard Olejnik

Minimizing 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

3 LIFL - Laboratoire d'Informatique Fondamentale de Lille

Abstract : The objective of this paper is first to properly define the notion of task clustering. This is the process of automatically mapping functionalities (blocks of code corresponding to a high-level feature) with real-time constraints to tasks (or threads). We aim at reducing the number of tasks functionalities are mapped to, while preserving the schedulability of the initial system. Second, our goal is to expose the complexity of the problem and to sketch methods we will propose for solving this problem. We consider independent tasks running on a single processor.

Keywords : real-time scheduling task clustering functionality to task mapping

Document type :

Conference papers

Domain :

Computer Science [cs] / Embedded Systems

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https://hal.inria.fr/hal-00874979
Contributor : Antoine Bertout <>
Submitted on : Sunday, October 20, 2013 - 3:04:43 PM
Last modification on : Thursday, February 21, 2019 - 10:52:54 AM
Long-term archiving on : Friday, April 7, 2017 - 1:30:46 PM

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