An Efficient Utilization-Based Test for Scheduling Hard Real-Time Sporadic DAG Task Systems on Multiprocessors

Zheng Dong, Cong Liu
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引用次数: 5

Abstract

The scheduling and schedulability analysis of real-time directed acyclic graph (DAG) task systems have received much recent attention. The DAG model can accurately represent intra-task parallelism and precedence constraints existing in many application domains. Existing techniques show that analyzing the DAG model is fundamentally more challenging compared to the ordinary sporadic task model, due to the complex intra-DAG precedence constraints which may cause rather pessimistic schedulability loss. However, such increased loss is counter-intuitive because the DAG structure shall better exploit the hardware parallelism provided by the multiprocessor platform. Our key observation is that the intra-DAG precedence constraints, if not carefully considered by the scheduling algorithm, may cause unpredictable execution behaviors of sub-tasks in a DAG and thus pessimistic analysis. In this paper, we present a set of novel scheduling and analysis techniques for better supporting hard real-time sporadic DAG tasks on multiprocessors, through smartly defining and analyzing the execution order of subtasks in each DAG. Combined with a new DAG-specific interval analysis framework, the proposed subtask ordering technique leads to a highly efficient utilization-based schedulability test. Importantly, the developed test becomes identical to the classical density test designed for the sporadic task model, if each DAG in the system has an out-degree of one (i.e., only containing a chain of subtasks). Experiments show the efficiency of the developed test, which improves schedulability upon existing utilization-based tests by over 60% on average and is often able to guarantee schedulability with little utilization loss.
基于高效利用率的多处理器硬实时零散DAG任务系统调度测试
实时有向无环图(DAG)任务系统的调度和可调度性分析近年来受到广泛关注。DAG模型可以准确地表示许多应用领域中存在的任务内并行性和优先性约束。现有的技术表明,分析DAG模型从本质上比分析普通的零散任务模型更具挑战性,因为DAG内部复杂的优先约束可能导致相当悲观的可调度性损失。然而,这种增加的损失是违反直觉的,因为DAG结构应该更好地利用多处理器平台提供的硬件并行性。我们的主要观察是,如果调度算法不仔细考虑DAG内的优先约束,可能会导致DAG中子任务的执行行为不可预测,从而导致悲观分析。在本文中,我们提出了一套新的调度和分析技术,通过智能地定义和分析每个DAG中的子任务的执行顺序,以更好地支持多处理器上的硬实时零散DAG任务。结合新的dag专用区间分析框架,提出的子任务排序技术可以实现高效的基于利用率的可调度性测试。重要的是,如果系统中的每个DAG的输出度为1(即仅包含一个子任务链),则开发的测试与为零星任务模型设计的经典密度测试相同。实验证明了所开发测试的效率,在现有基于利用率的测试基础上平均提高了60%以上的可调度性,并且通常能够在很少的利用率损失的情况下保证可调度性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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