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Reliability guaranteed energy-aware frame-based task set execution strategy for hard real-time systems

机译:硬实时系统的可靠性保证基于能量感知的基于框架的任务集执行策略

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In this paper, we study the problem of how to execute a real-time frame-based task set on DVFS-enabled processors so that the system's reliability can be guaranteed and the energy consumption of executing the task set is minimized. To ensure the reliability requirement, processing resources are reserved to re-execute tasks when transient faults occur. However, different from commonly used approaches that the reserved processing resources are shared by all tasks in the task set, we judiciously select a subset of tasks to share these reserved resources for recovery purposes. In addition, we formally prove that for a give task set, the system achieves the highest reliability and consumes the least amount of energy when the task set is executed with a uniform frequency (or neighboring frequencies if the desired frequency is not available). Based on the theoretic conclusion, rather than heuristically searching for appropriate execution frequency for each individual task as used in many research work, we directly calculate the optimal execution frequency for the task set. Our simulation results have shown that with our approach, we can not only guarantee the same level of system reliability, but also have up to 15% energy saving improvement over other fault recovery-based approaches existed in the literature. Furthermore, as our approach does not require frequent frequency changes, it works particularly effective on processors where frequency switching overhead is large and not negligible.
机译:在本文中,我们研究了如何在支持DVFS的处理器上执行基于帧的实时任务集的问题,从而可以保证系统的可靠性并最大程度地减少执行任务集的能耗。为确保可靠性要求,当出现瞬时故障时,将保留处理资源以重新执行任务。但是,与常用方法不同,保留的处理资源由任务集中的所有任务共享,我们明智地选择任务的子集以共享这些保留的资源以用于恢复。此外,我们正式证明,对于给定的任务集,当以统一的频率(或所需频率不可用时,则为相邻频率)执行任务集时,系统可获得最高的可靠性并消耗最少的能量。基于理论上的结论,我们没有像许多研究工作中那样针对每个单独的任务试探性地搜索适当的执行频率,而是直接计算任务集的最佳执行频率。仿真结果表明,采用这种方法,我们不仅可以保证相同水平的系统可靠性,而且与文献中存在的其他基于故障恢复的方法相比,还可以节省多达15%的能源。此外,由于我们的方法不需要频繁的频率更改,因此它在频率切换开销较大且不可忽略的处理器上特别有效。

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