A Fully Polynomial Time Approximation Scheme for Adaptive Variable Rate Task Demand

dc.contributor.authorWillcock, Aaronen
dc.contributor.authorFisher, Nathanen
dc.contributor.authorChantem, Thidapat (Tam)en
dc.date.accessioned2025-02-06T18:36:10Zen
dc.date.available2025-02-06T18:36:10Zen
dc.date.issued2024-11-06en
dc.date.updated2025-02-01T09:06:55Zen
dc.description.abstractThe Adaptive Variable Rate (AVR) task model defines a task where job WCET and period are a function of engine speed. Motivated by a lack of tractable AVR task demand methods, this work uses predefined job sequences for the Bounded Precedence Constraint Knapsack Problem inherent in AVR task demand calculation instead of enumerating all considered speeds as in existing work. A new, exact approach is proposed and approximated, enabling the derivation of a Fully Polynomial Time Approximation Scheme that outperforms the state-of-the-art in runtime (7,800x improvement) and RAM use (99% reduction) with less than 8% demand overestimate.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1145/3696355.3696367en
dc.identifier.urihttps://hdl.handle.net/10919/124521en
dc.language.isoenen
dc.publisherACMen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.holderThe author(s)en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleA Fully Polynomial Time Approximation Scheme for Adaptive Variable Rate Task Demanden
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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