Real-Time Dynamic Power Management through Device Forbidden Regions

V. Devadas, Hakan Aydin
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引用次数: 39

Abstract

Dynamic power management (DPM) techniques are crucial in minimizing the overall energy consumption in real-time embedded systems. The timing constraints of real-time applications and non-trivial time/energy transition overheads introduce significant challenges, as the device sleep intervals should be longer than a minimum threshold (called the break-even time) to ensure energy-efficiency. In this paper, we present a novel approach to the real-time DPM problem by explicitly enforcing long device sleep intervals for different devices, called device forbidden regions. We focus on the application of our technique to task systems with rate-monotonic priorities, and develop our algorithm DFR-RMS. Our solution includes a static component where the duration and frequency of forbidden regions are determined through the extended time-demand analysis to preserve the temporal correctness of all the tasks, while enhancing the energy savings. Then, we present a sophisticated on-line component which interacts with existing prediction-based DPM schemes to realize the full potential of device forbidden regions. Further, our scheme can be used with or without dynamic voltage scaling (DVS). Our experimental evaluation hints that significant energy gains can be obtained, when compared to the existing prediction-based techniques. Another contribution of this research effort is to show that the general problem of generating feasible schedules for preemptive periodic real-time tasks where all device sleep intervals are longer than the device break-even times is NP-hard in the strong sense.
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通过设备禁用区域实时动态电源管理
动态电源管理(DPM)技术对于降低实时嵌入式系统的总体能耗至关重要。实时应用程序的时间限制和重要的时间/能量转换开销带来了重大挑战,因为设备睡眠间隔应该长于最小阈值(称为盈亏平衡时间),以确保能源效率。在本文中,我们提出了一种解决实时DPM问题的新方法,通过显式地强制不同设备的长设备睡眠间隔,称为设备禁止区域。我们将该技术应用于具有速率单调优先级的任务系统,并开发了我们的DFR-RMS算法。我们的解决方案包括一个静态组件,其中禁止区域的持续时间和频率是通过扩展的时间需求分析来确定的,以保持所有任务的时间正确性,同时提高能源节约。然后,我们提出了一个复杂的在线组件,该组件与现有的基于预测的DPM方案交互,以充分发挥设备禁止区域的潜力。此外,我们的方案可以使用或不使用动态电压缩放(DVS)。我们的实验评估提示,与现有的基于预测的技术相比,可以获得显著的能量增益。本研究工作的另一个贡献是表明,在所有设备睡眠间隔都大于设备收支平衡时间的情况下,为抢占式周期性实时任务生成可行调度的一般问题在强意义上是np困难的。
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