Task reweighting under global scheduling on multip

Authors: Aaron Block James H Anderson UmaMaheswari C Devi

Publish Date: 2007/11/27

Volume: 39, Issue: 1-3, Pages: 123-167

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Abstract

We consider schemes for enacting task share changes—a process called reweighting—on realtime 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 partitioningbased scheduling algorithms can reweight tasks with better averagecase performance but greater error However preemption and migration overheads can be high in fair schemes In this paper we consider the question of whether nonfair earliestdeadlinefirst mathsfEDF global scheduling techniques can improve the accuracy of reweighting relative to partitioningbased schemes and provide improved averagecase performance relative to fairscheduled systems Our conclusion is that for soft realtime systems global mathsfEDF schemes provide a good mix of accuracy and averagecase performance

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