Agrawa, Kunal, Baruah, Sanjoy and Burns, Alan orcid.org/0000-0001-5621-8816 (2020) Semi-Clairvoyance in Mixed-Criticality Scheduling. In: 2019 IEEE Real-Time Systems Symposium (RTSS). 40th IEEE Real-Time Systems Symposium (RTSS 2019), 01 Dec 2019 IEEE Real-Time Systems Symposium (RTSS) . IEEE , pp. 458-468.
Abstract
In the Vestal model of mixed-criticality systems, jobs are characterized by multiple different estimates of their actual, but unknown, worst-case execution time (WCET) parameters. Prior work on mixed-criticality scheduling theory assumes that the execution duration of a job is only revealed by actually executing the job through to completion. We consider a different *semi-clairvoyant* model here, in which it is assumed that upon arrival a job reveals which of its WCET parameters it will respect. We identify circumstances under which this is a reasonable model, and design and evaluate scheduling algorithms appropriate for this model. We show that such semi-clairvoyance yields a significant quantifiable benefit over non-clairvoyance, in terms of both the complexity of schedulability analysis and the speedup needed to ensure schedulability.
Metadata
Item Type: | Proceedings Paper | ||||||
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Copyright, Publisher and Additional Information: | This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details. |
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Dates: |
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Institution: | The University of York | ||||||
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) | ||||||
Funding Information: |
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Depositing User: | Pure (York) | ||||||
Date Deposited: | 09 Oct 2019 09:40 | ||||||
Last Modified: | 16 Apr 2024 23:05 | ||||||
Published Version: | https://doi.org/10.1109/RTSS46320.2019.00047 | ||||||
Status: | Published | ||||||
Publisher: | IEEE | ||||||
Series Name: | IEEE Real-Time Systems Symposium (RTSS) | ||||||
Refereed: | No | ||||||
Identification Number: | https://doi.org/10.1109/RTSS46320.2019.00047 |