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Scheduling Real-Time Multi-Processor Systems with Distance-Constrained Tasks Using the Early-Release-Fair Model

机译:使用早期发布公平模型调度具有距离受限任务的实时多处理器系统

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摘要

A hard real-time system is one whose correctness depends not only on the logical result, but also when the results are produced. While many techniques have been proposed for single processor real-time systems, multiprocessor systems have not been studied so extensively. In this paper, we mainly propose two variant (DCTS) by using the Early-Release-Fair (ERfair) and Proportionate-fair (Pfair) model with integral assumptions for identical multi-processor real-time systems. ERfair is a scheduling model for real-time tasks on a multiprocessor system. On the different definitions of distance constraint, we propose two efficient scheduling algorithms designed to probe whether the distance constraints of all ER-fair tasks can be guaranteed. If the distance constraints cannot be guaranteed, then the proposed algorithms gather the unfeasible tasks and inflate them with a reweighting function. The proposed algorithms are linear-time and most suitable for dynamic systems. The experimental results reveal that the proposed algorithms increase significantly the ratio of schedulable task sets.
机译:硬实时系统的正确性不仅取决于逻辑结果,而且还取决于结果的产生时间。尽管已经针对单处理器实时系统提出了许多技术,但是对多处理器系统的研究还不够广泛。在本文中,我们主要通过使用早期发布公平(ERfair)模型和比例公平(Pfair)模型,并针对相同的多处理器实时系统的整体假设,提出两个变体(DCTS)。 ERfair是用于多处理器系统上实时任务的调度模型。针对距离约束的不同定义,我们提出了两种有效的调度算法,旨在探究是否可以保证所有ER公平任务的距离约束。如果不能保证距离约束,则所提出的算法会收集不可行的任务,并使用重加权函数将其膨胀。所提出的算法是线性时间的,并且最适合于动态系统。实验结果表明,该算法显着提高了可调度任务集的比例。

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