Abstract
We consider schemes for enacting task share changes—a process called reweighting—on real-time multiprocessor platforms. Our particular focus is reweighting schemes that are deployed in environments in which tasks may frequently request significant share changes. Prior work has shown that fair scheduling algorithms are capable of reweighting tasks with minimal allocation error and that partitioning-based scheduling algorithms can reweight tasks with better average-case performance, but greater error. However, preemption and migration overheads can be high in fair schemes. In this paper, we consider the question of whether non-fair, earliest-deadline-first ( \(\mathsf{EDF}\) ) global scheduling techniques can improve the accuracy of reweighting relative to partitioning-based schemes and provide improved average-case performance relative to fair-scheduled systems. Our conclusion is that, for soft real-time systems, global \(\mathsf{EDF}\) schemes provide a good mix of accuracy and average-case performance.
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Work supported by NSF grants CCR 0204312, CNS 0309825, CNS 0408996, and CCF 0541056. The first and third authors were also supported by an NSF fellowship and an IBM Ph.D. fellowship, respectively.
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Block, A., Anderson, J.H. & Devi, U.C. Task reweighting under global scheduling on multiprocessors. Real-Time Syst 39, 123–167 (2008). https://doi.org/10.1007/s11241-007-9041-2
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DOI: https://doi.org/10.1007/s11241-007-9041-2