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dc.contributor.authorAmurrio, Andoni
dc.contributor.authorGutiérrez García, José Javier 
dc.contributor.authorAldea Rivas, Mario 
dc.contributor.authorAzketa, Ekain
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2023-05-30T09:00:05Z
dc.date.available2023-05-30T09:00:05Z
dc.date.issued2022-12-07
dc.identifier.urihttps://hdl.handle.net/10902/29141
dc.description.abstractIn this work, a solution that can be applied to the RTSS 2022’s Industry Challenge is proposed. It relies on a real-time system model and a set of schedulability analysis and optimization tools, enabling the design of safety-critical applications compliant with timing requirements. The presented toolchain is enhanced with a novel task allocation technique, which leverages sensitivity analysis and that can be applied to heterogeneous systems, to provide promising solutions that improve state-of-the-art algorithms’ performance.es_ES
dc.description.sponsorshipThis work was supported in part by MCIN/ AEI /10.13039/501100011033/ FEDER “Una manera de hacer Europa” under grant PID2021-124502OB-C42 (PRESECREL).es_ES
dc.format.extent271 KBes_ES
dc.language.isoenges_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.source43rd IEEE Real-Time Systems Symposium (RTSS) 2022, Industry Challengees_ES
dc.subject.otherMASTes_ES
dc.subject.otherSchedulability analysises_ES
dc.subject.otherOptimizationes_ES
dc.subject.otherPartitioninges_ES
dc.titleOptimization in Heterogeneous Distributed Real-Time Systems based on Partitioninges_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsopenAccesses_ES
dc.type.versionacceptedVersiones_ES


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Attribution-NonCommercial-NoDerivatives 4.0 InternationalExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 International