基于自定时和周期调度的嵌入式流应用混合调度算法

A. Dkhil, XuanKhanh Do, Stéphane Louise, Christine Rochange
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引用次数: 6

摘要

在本文中,我们考虑了以非循环数据流图为模型的安全关键流应用的多处理器调度问题。据我们所知,大多数已有的研究都提出了忽略延迟甚至可能对延迟产生负面影响的周期调度,其结果与自定时调度(Self-Timed scheduling, STS)的结果相差甚远。本文提出了一种新的调度策略自定时周期(STP),它是一种将自定时调度与周期调度相结合的执行模型。所提出的框架表明,这两种策略的使用是可能的,并且它们相互补充,STS提高了程序的性能指标,而周期模型则捕获了时序方面。我们为一组10个现实生活中的流媒体应用程序评估了调度策略的性能。我们发现,在大多数情况下,与静态周期计划(SPS)相比,我们的方法在延迟方面有显着改善,并且结果接近STS的最佳情况延迟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Hybrid Scheduling Algorithm Based on Self-Timed and Periodic Scheduling for Embedded Streaming Applications
In this paper, we consider the problem of multiprocessor scheduling for safety-critical streaming applications modeled as acyclic data-flow graphs. To the best of our knowledge, most existing works have proposed periodic scheduling that ignore latency or can even have a negative impact on it: the results are quite far from those obtained under Self-Timed scheduling (STS). In this paper, we introduce a new scheduling policy noted Self-Timed Periodic (STP), which is an execution model combining self-timed scheduling with periodic scheduling. The proposed framework shows that the use of both strategies is possible and that they complement each other, STS improves the performance metrics of the programs, while the periodic model captures the timing aspects. We evaluate the performance of our scheduling policy for a set of 10 real-life streaming applications. We find that in most of the cases, our approach gives a significant improvement in latency compared to the Static Periodic Schedule (SPS), and results which are close to the best case latency of STS.
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