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        <datestamp>2024-03-06T10:49:48Z</datestamp>
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          <dc:title>Improving the Accuracy of Cache-Aware Response Time Analysis Using Preemption Partitioning</dc:title>
          <dc:creator>Marković, Filip</dc:creator>
          <dc:creator>Carlson, Jan</dc:creator>
          <dc:creator>Altmeyer, Sebastian</dc:creator>
          <dc:creator>Dobrin, Radu</dc:creator>
          <dc:subject>Real-time systems</dc:subject>
          <dc:subject>Fixed-Priority Preemptive Scheduling</dc:subject>
          <dc:subject>Preemption delay</dc:subject>
          <dc:description>Schedulability analyses for preemptive real-time systems need to take into account cache-related preemption delays (CRPD) caused by preemptions between the tasks. The estimation of the CRPD values must be sound, i.e. it must not be lower than the worst-case CRPD that may occur at runtime, but also should minimise the pessimism of estimation. The existing methods over-approximate the computed CRPD upper bounds by accounting for multiple preemption combinations which cannot occur simultaneously during runtime. This over-approximation may further lead to the over-approximation of the worst-case response times of the tasks, and therefore a false-negative estimation of the system’s schedulability. In this paper, we propose a more precise cache-aware response time analysis for sporadic real-time systems under fully-preemptive fixed priority scheduling. The evaluation shows a significant improvement over the existing state of the art approaches.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Filip Marković and Jan Carlson and Sebastian Altmeyer and Radu Dobrin</dc:contributor>
          <dc:date>2020</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 165, 32nd Euromicro Conference on Real-Time Systems (ECRTS 2020)</dc:relation>
          <dc:type>InProceedings</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.ECRTS.2020.5</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-123682</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2020.5</dc:identifier>
          <dc:language>eng</dc:language>
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