Many of today’s embedded devices, e.g. pacemakers or nodes in a monitoring sensor network, are expected to work energy perpetual, i.e. to be self-powered by energy harvesting from renewable sources. The major issue of such systems is the uncertainty of the available energy, influencing the application performance predictability. In many such applications, different performance levels are defined according to the patterns of job skipping. This paper proposes a performance maximization method for self-powered energy-intermittent (m, k)-firm systems via appropriate switching between the performance levels. To formally examine the impact of performance switch time on the performance-related criteria, we introduce the energy supply and energy demand functions. A sufficient schedulability test for one hyperperiod is also proposed for the preemptive fixed-priority as-soon-as-possible (PFPASAP\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$PFP_{ASAP}$$\end{document}) scheduling algorithm under variable-rate energy harvesting. We then propose a performance maximization heuristic, and compare its effectiveness to the optimal performance. The extensive simulations show that our proposed method is fast, whereas it effectively approximates the optimal solution.

中文翻译：

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能量可变自供电 (m, k)-firm 实时系统的性能最大化

当今的许多嵌入式设备，例如起搏器或监控传感器网络中的节点，都有望永久使用能源，即通过从可再生能源收集能量来自供电。此类系统的主要问题是可用能量的不确定性，影响应用程序性能的可预测性。在许多此类应用程序中，根据作业跳过的模式定义了不同的性能级别。本文提出了一种通过性能水平之间的适当切换来实现自供电能源间歇（m，k）公司系统的性能最大化方法。为了正式检查性能切换时间对性能相关标准的影响，我们引入了能源供应和能源需求函数。对于一个超周期的足够的可调度性测试也被提议用于抢占式固定优先级尽快（PFPASAP\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage {amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$PFP_{ASAP}$$\end{document}) 调度算法下可变速率能量收集。然后我们提出了一种性能最大化启发式方法，并将其有效性与最佳性能进行比较。大量的模拟表明我们提出的方法是快速的，而它有效地逼近了最优解。