TY - GEN
T1 - Modular Performance Analysis of Energy-Harvesting Real-Time Networked Systems
AU - Guan, Nan
AU - Zhao, Mengying
AU - Xue, Chun Jason
AU - Liu, Yongpan
AU - Yi, Wang
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/1/14
Y1 - 2016/1/14
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/84964595977
U2 - 10.1109/RTSS.2015.14
DO - 10.1109/RTSS.2015.14
M3 - 会议稿件
AN - SCOPUS:84964595977
T3 - Proceedings - Real-Time Systems Symposium
SP - 65
EP - 74
BT - Proceedings - 2015 IEEE 36th Real-Time Systems Symposium, RTSS 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 36th IEEE Real-Time Systems Symposium, RTSS 2015
Y2 - 1 December 2015 through 4 December 2015
ER -