实时嵌入式系统中全系统能量最小化的动态电压缩放

R. Jejurikar, Rajesh K. Gupta
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引用次数: 182

摘要

传统上,动态电压缩放(DVS)技术侧重于最小化处理器能耗,而不是整个系统能耗。分布式交换机导致的速度变慢会增加内存和网络接口等组件的能耗。此外,随着缩放装置技术的发展,泄漏功耗也在不断增加,这也是必须考虑的问题。在这项工作中,我们考虑了实时任务系统中的节能减速。提出了一种基于处理器泄漏和系统资源待机能耗贡献的任务减速因子计算算法。我们使用随机生成任务集的仿真实验显示,与传统的动态电压缩放相比,平均能量增益为10%。我们进一步将减速与拖延计划结合起来,这将平均节省15%的能源。我们表明,我们的调度方法最大限度地减少了系统范围内资源的静态和动态总能耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic voltage scaling for systemwide energy minimization in real-time embedded systems
Traditionally, dynamic voltage scaling (DVS) techniques have focused on minimizing the processor energy consumption as opposed to the entire system energy consumption. The slowdown resulting from DVS can increase the energy consumption of components like memory and network interfaces. Furthermore, the leakage power consumption is increasing with the scaling device technology and must also be taken into account. In this work, we consider energy efficient slowdown in a real-time task system. We present an algorithm to compute task slowdown factors based on the contribution of the processor leakage and standby energy consumption of the resources in the system. Our simulation experiments using randomly generated task sets show on an average 10% energy gains over traditional dynamic voltage scaling. We further combine slowdown with procrastination scheduling which increases the average energy savings to 15%. We show that our scheduling approach minimizes the total static and dynamic energy consumption of the systemwide resources.
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