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Improved Carry-in Workload Estimation for Global Multiprocessor Scheduling

机译:全局多处理器调度的改进的随身工作量估计

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As an important and fundamental tool for analyzing the schedulability of a real-time task set on the multiprocessor platform, response time analysis (RTA) has been researched for several years on both Global Fixed Priority (G-FP) and Global Earliest Deadline First (G-EDF) scheduling. This paper proposes a new analysis that improves over current state-of-the-art RTA methods for both G-FP and G-EDF scheduling, by reducing their pessimism. The key observation is that when estimating the carry-in workload, all the existing RTA techniques depend on the worst case scenario in which the carry-in job should execute as late as possible and just finishes execution before its worst case response time (WCRT). But the carry-in workload calculated under this assumption may be over-estimated, and thus the accuracy of the response time analysis may be impacted. To address this problem, we first propose a new method to estimate the carry-in workload more precisely. The proposed method does not depend on any specific scheduling algorithm and can be used for both G-FP and G-EDF scheduling. We then propose a general RTA algorithm that can improve most existing RTA tests by incorporating our carry-in estimation method. To further improve the execution efficiency, we also introduce an optimization technique for our RTA tests. Experiments with randomly generated task sets are conducted and the results show that, compared with the state-of-the-art technologies, the proposed tests exhibit considerable performance improvements, up to 9 and 7.8 percent under G-FP and G-EDF scheduling respectively, in terms of schedulability test precision.
机译:作为分析多处理器平台上实时任务的可调度性的重要基础工具,响应时间分析(RTA)在全球固定优先级(G-FP)和全球最早截止日期优先( G-EDF)计划。本文提出了一种新的分析方法,该方法通过减少悲观情绪,改进了针对G-FP和G-EDF调度的最新RTA方法。关键观察结果是,在估计随身携带的工作量时,所有现有的RTA技术都取决于最坏情况,在这种情况下,随身携带的工作应尽可能晚地执行,并在其最坏情况响应时间(WCRT)之前完成执行。但是,在此假设下计算出的随身携带工作量可能会被高估,因此响应时间分析的准确性可能会受到影响。为了解决这个问题,我们首先提出一种新方法来更精确地估计随身携带的工作量。所提出的方法不依赖于任何特定的调度算法,并且可以用于G-FP和G-EDF调度。然后,我们提出了一种通用的RTA算法,该算法可以通过合并我们的随身估计方法来改善大多数现有的RTA测试。为了进一步提高执行效率,我们还为RTA测试引入了一种优化技术。进行了随机生成的任务集的实验,结果表明,与最新技术相比,所提出的测试具有显着的性能改进,在G-FP和G-EDF调度下分别达到了9%和7.8%。 ,在可调度性测试精度方面。

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