Modular Performance Analysis of Energy-Harvesting Real-Time Networked Systems

Nan Guan, Mengying Zhao, C. Xue, Yongpan Liu, W. Yi
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引用次数: 6

Abstract

This paper studies the performance analysis problem of energy-harvesting real-time network systems in the Real-Time Calculus (RTC) framework. The behavior of an energy-harvesting node turns out to be a generalization of two known components in RTC: it behaves like an AND connector if the capacitor used to temporally store surplus energy has unlimited capacity and there is no energy loss, while it behaves like a greedy processing component (GPC) if the size of the capacitor is zero and thus surplus energy is lost or passed to other nodes immediately. In this paper, methods are developed to analyze the worst-case performance, in terms of delay and backlog, of energy-harvesting nodes as well as compute upper/lower bounds of their data and energy outputs. Moreover, with the proposed analysis methods, we disclose some interesting properties of the worst-case behaviors of energy-harvesting systems, which provide useful information to guide system design. Experiments are conducted to evaluate our theoretical contributions and also confirm that the disclosed properties are not just the result of our analysis, but indeed hold in realistic system behaviors.
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能量采集实时网络化系统的模块化性能分析
本文研究了实时微积分(real-time Calculus, RTC)框架下能量采集实时网络系统的性能分析问题。能量收集节点的行为是RTC中两个已知组件的概括:如果用于暂时存储剩余能量的电容器具有无限容量并且没有能量损失,则它的行为就像AND连接器,而如果电容器的大小为零,则它的行为就像贪婪处理组件(GPC),因此剩余能量丢失或立即传递给其他节点。本文提出了能量收集节点在延迟和积压情况下的最坏情况性能分析方法,并计算了其数据和能量输出的上/下界。此外,通过所提出的分析方法,我们揭示了能量收集系统最坏情况行为的一些有趣特性,为指导系统设计提供了有用的信息。我们进行了实验来评估我们的理论贡献,并确认所披露的性质不仅仅是我们分析的结果,而且确实适用于现实的系统行为。
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