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容错条件下对基于有向无环图的应用的最坏完成时间分析

Worst-Case Finish Time Analysis for DAG-Based Applications in the Presence of Transient Faults

  • 摘要: 硬实时系统中的应用即使在出现暂时性错误的时候也要足预设截止时间的要求,因此对其最坏完成时间的分析必须将由于任务出错重新执行产生的额外时间考虑在内。然而现存的完成时间分析技术只能估计最坏完成时间并且通常低估或高估应用的完成时间。在本次工作中,我们推导出一个任务集合在它的关键任务发生所有可能的错误将会导致该任务集合具有最坏完成时间。我们提出了一种可以在O(|V|+|E|)内找出关键任务和计算出最坏完成时间的方法,其中|V|和|E>|分别代表任务的个数和任务之间的依赖关系。该方法能够应用于一系列具有故障倾向的多处理器系统进而测试基于有向无环图的应用的可行性,其中处理器是否异构或者是否支持动态电压调整都是可行的。和提出的方法具有相同时间复杂度的两个常犯的错误是低估或者高估最坏完成时间,实验表明低估或者高估的最坏完成时间分别可以达到25%和13%。同时基于提出的关键任务技术和一个任务集合,我们用模拟退化算法来寻找节能、容错的调度序列。实验结果表明,提出的关键任务技术相比于高估最坏完成时间可以节省高达40%的能耗。

     

    Abstract: Tasks in hard real-time systems are required to meet preset deadlines, even in the presence of transient faults, and hence the analysis of worst-case finish time (WCFT) must consider the extra time incurred by re-executing tasks that were faulty. Existing solutions can only estimate WCFT and usually result in significant under- or over-estimation. In this work, we conclude that a sufficient and necessary condition of a task set experiencing its WCFT is that its critical task incurs all expected transient faults. A method is presented to identify the critical task and WCFT in O(|V|+|E|) where |V| and |E| are the number of tasks and dependencies between tasks, respectively. This method finds its application in testing the feasibility of directed acyclic graph (DAG) based task sets scheduled in a wide variety of fault-prone multi-processor systems, where the processors could be either homogeneous or heterogeneous, DVS-capable or DVS-incapable, etc. The common practices, which require the same time complexity as the proposed critical-task method, could either underestimate the worst case by up to 25%, or overestimate by 13%. Based on the proposed critical-task method, a simulated-annealing scheduling algorithm is developed to find the energy efficient fault-tolerant schedule for a given DAG task set. Experimental results show that the proposed critical-task method wins over a common practice by up to 40% in terms of energy saving.

     

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