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Scheduling of mixed-criticality systems with RUN

Authors: Romain Gratia; Thomas Robert 0003; Laurent Pautet;

Scheduling of mixed-criticality systems with RUN

Abstract

Mixed-criticality systems emerged with the aim of reconciling safety requirements and efficient use of multi-processor or uniprocessor platforms. On multi-processors, recent works on mixed-criticality have produced impressive results in terms of speed-up factor. But these solutions, based on Pfair-like scheduling algorithms, entail too many preemptions and migrations to be effectively used in real systems. As RUN is an optimal scheduling algorithm that is known to limit this problem, we propose MxC-RUN, an adaptation of RUN to mixed-criticality systems. We redefine RUN's primal servers as modal servers that allocate the overestimated time budget of their higher criticality tasks to execute lower criticality ones. These servers can be handled by RUN without any modification and preserve its performances in terms of preemptions and migrations. MxC-RUN earns a speed-up factor smaller than other multi-processors EDF-based mixed-criticality scheduling algorithms.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
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