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A hybrid performance analysis technique for distributed real-time embedded systems

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dc.contributor.authorChoi, Junchul-
dc.contributor.authorOh, Hyunok-
dc.contributor.authorHa, Soonhoi-
dc.date.accessioned2022-07-11T15:49:33Z-
dc.date.available2022-07-11T15:49:33Z-
dc.date.created2021-05-12-
dc.date.issued2018-07-
dc.identifier.issn0922-6443-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/149730-
dc.description.abstractIt remains a challenging problem to tightly estimate the worst-case response time of an application in a distributed embedded system, especially when there are dependencies between tasks. Recently, a holistic worst-case response time analysis approach called scheduling time bound analysis has been proposed to find a tight upper bound of the worst-case response times of applications specified by a set of task graphs. Since it assumes that the starting offsets of applications are known and fixed, it fails to make a tight estimation despite increased computation time when the starting offsets are dynamic. To overcome this problem, we propose a novel conservative performance analysis, called hybrid performance analysis, combining the response time analysis technique and the scheduling time bound analysis technique to compute a tighter bound faster. The proposed scheme is proven to be conservative formally. Through extensive experiments with real-life benchmarks and synthetic examples, the superior performance of our proposed approach compared with previous methods is confirmed.-
dc.language영어-
dc.language.isoen-
dc.publisherSPRINGER-
dc.titleA hybrid performance analysis technique for distributed real-time embedded systems-
dc.typeArticle-
dc.contributor.affiliatedAuthorOh, Hyunok-
dc.identifier.doi10.1007/s11241-018-9307-x-
dc.identifier.scopusid2-s2.0-85045242936-
dc.identifier.wosid000437005100003-
dc.identifier.bibliographicCitationREAL-TIME SYSTEMS, v.54, no.3, pp.562 - 604-
dc.relation.isPartOfREAL-TIME SYSTEMS-
dc.citation.titleREAL-TIME SYSTEMS-
dc.citation.volume54-
dc.citation.number3-
dc.citation.startPage562-
dc.citation.endPage604-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science-
dc.relation.journalWebOfScienceCategoryTheory & Methods-
dc.subject.keywordPlusSCHEDULABILITY ANALYSIS-
dc.subject.keywordAuthorWorst-case response time-
dc.subject.keywordAuthorPerformance analysis-
dc.subject.keywordAuthorResponse time analysis-
dc.subject.keywordAuthorPartitioned scheduling-
dc.subject.keywordAuthorData dependency-
dc.subject.keywordAuthorTask graph-
dc.identifier.urlhttps://link.springer.com/article/10.1007/s11241-018-9307-x-
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