License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ECRTS.2018.5
URN: urn:nbn:de:0030-drops-89999
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/8999/
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Agrawal, Kunal ; Baruah, Sanjoy

A Measurement-Based Model for Parallel Real-Time Tasks

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LIPIcs-ECRTS-2018-5.pdf (0.5 MB)

Abstract

Under the federated paradigm of multiprocessor scheduling, a set of processors is reserved for the exclusive use of each real-time task. If tasks are characterized very conservatively (as is typical in safety-critical systems), it is likely that most invocations of the task will have computational demand far below the worst-case characterization, and could have been scheduled correctly upon far fewer processors than were assigned to it assuming the worst-case characterization of its run-time behavior. Provided we could safely determine during run-time when all the processors are going to be needed, for the rest of the time the unneeded processors could be idled in low-energy "sleep" mode, or used for executing non-real time work in the background. In this paper we propose a model for representing parallelizable real-time tasks in a manner that permits us to do so. Our model does not require us to have fine-grained knowledge of the internal structure of the code represented by the task; rather, it characterizes each task by a few parameters that are obtained by repeatedly executing the code under different conditions and measuring the run-times.

BibTeX - Entry

@InProceedings{agrawal_et_al:LIPIcs:2018:8999,
  author =	{Kunal Agrawal and Sanjoy Baruah},
  title =	{{A Measurement-Based Model for Parallel Real-Time Tasks}},
  booktitle =	{30th Euromicro Conference on Real-Time Systems (ECRTS 2018)},
  pages =	{5:1--5:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-075-0},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{106},
  editor =	{Sebastian Altmeyer},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2018/8999},
  URN =		{urn:nbn:de:0030-drops-89999},
  doi =		{10.4230/LIPIcs.ECRTS.2018.5},
  annote =	{Keywords: multiprocessor federated scheduling, parallel tasks, work and span, mixed criticality}
}

Keywords: multiprocessor federated scheduling, parallel tasks, work and span, mixed criticality
Collection: 30th Euromicro Conference on Real-Time Systems (ECRTS 2018)
Issue Date: 2018
Date of publication: 22.06.2018

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