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CPMD-mindful task assignment for NPS-F

dc.contributor.authorNelissen, Geoffrey
dc.contributor.authorBletsas, Konstantinos
dc.contributor.authorGoossens, Joel
dc.date.accessioned2015-01-15T10:51:07Z
dc.date.available2015-01-15T10:51:07Z
dc.date.issued2014
dc.description.abstractThe multiprocessor scheduling scheme NPS-F for sporadic tasks has a high utilisation bound and an overall number of preemptions bounded at design time. NPS-F binpacks tasks offline to as many servers as needed. At runtime, the scheduler ensures that each server is mapped to at most one of the m processors, at any instant. When scheduled, servers use EDF to select which of their tasks to run. Yet, unlike the overall number of preemptions, the migrations per se are not tightly bounded. Moreover, we cannot know a priori which task a server will be currently executing at the instant when it migrates. This uncertainty complicates the estimation of cache-related preemption and migration costs (CPMD), potentially resulting in their overestimation. Therefore, to simplify the CPMD estimation, we propose an amended bin-packing scheme for NPS-F allowing us (i) to identify at design time, which task migrates at which instant and (ii) bound a priori the number of migrating tasks, while preserving the utilisation bound of NPS-F.por
dc.identifier.doi10.1007/s11241-014-9206-8
dc.identifier.issn0922-6443
dc.identifier.issn1573-1383
dc.identifier.urihttp://hdl.handle.net/10400.22/5410
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherSpringerpor
dc.relation.ispartofseriesReal-Time Systems;Vol. 50, Issue 5-6
dc.relation.publisherversionhttp://link.springer.com/article/10.1007%2Fs11241-014-9206-8por
dc.subjectReal-time schedulingpor
dc.subjectMultiprocessorpor
dc.subjectSemi-partitionedpor
dc.subjectNPS-Fpor
dc.subjectBin packingpor
dc.subjectCPMD estimationpor
dc.titleCPMD-mindful task assignment for NPS-Fpor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage591por
oaire.citation.startPage585por
rcaap.rightsopenAccesspor
rcaap.typearticlepor

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