Elastic Scheduling for Fixed-Priority Constrained-Deadline Tasks
Elastic Scheduling for Fixed-Priority Constrained-Deadline Tasks
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DOI：
10.1109/isorc58943.2023.00014
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发表时间：
2023-05
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影响因子：
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通讯作者：
M. Sudvarg;Sanjoy Baruah;Chris Gill
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文献类型：
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作者：
M. Sudvarg;Sanjoy Baruah;Chris Gill
弹性调度为系统提供了一种模型，在这种模型中，尽管资源有限，单个任务的利用率仍然可以适应以保证可调度性。每个任务的特点是一系列可接受的利用率和“弹性常数”，代表其灵活性，以减少或“压缩”其利用率从所需的最大值。利用率压缩通过延长任务周期或减少工作负载来实现。本文将该模型扩展到单处理器上调度的固定优先级约束截止期任务系统的周期压缩问题。我们提出了两个近似算法和一个最佳算法来确定模型下的压缩。然后，我们比较了所有三个的执行时间和精度，表明即使是大型任务集，在线压缩可以在低功耗的嵌入式系统上进行可行的。
Elastic scheduling provides a model for systems in which individual task utilizations can adapt to guarantee schedulability despite limited resources. Each task is characterized by a range of acceptable utilizations and an “elastic constant” representing its flexibility to reduce or “compress” its utilization from the desired maximum. Utilization compression is realized by either extending task periods or reducing workloads. This paper extends the model to address period compression for fixed-priority constrained-deadline task systems scheduled on a uniprocessor. We propose two approximate algorithms and one optimal algorithm for determining compression under the model. We then compare the execution times and accuracies of all three, demonstrating that even for large task sets, online compression can be performed feasibly on low-powered embedded systems.