A Compositional Framework for Quantitative Online Monitoring over Continuous-Time Signals

A Compositional Framework for Quantitative Online Monitoring over Continuous-Time Signals
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连续时间信号定量在线监测的组合框架

DOI:
10.1007/978-3-030-88494-9_8
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发表时间:
2021
期刊:
Runtime Verification 2021
影响因子:
--
通讯作者:
Wang, Zhifu
Wang, Zhifu
中科院分区:
--
文献类型:
--
作者:
Mamouras, Konstantinos;Chattopadhyay, Agnishom;Wang, Zhifu

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我们研究了密集时间和连续时间信号的在线监测算法,用于度量时间逻辑(MTL)的属性。我们考虑了一个基于完全格的抽象代数语义,它包含布尔(定性)语义和实值鲁棒(定量)语义。我们的语义还扩展到部分有序的真值,并允许在满足中建模不确定性。我们提出了一种基于一类无限状态确定性信号传感器构建在线监视器的组合方法,该传感器(1)允许产生相对于输入信号具有有界延迟的输出信号,并且(2)在输出信号中不引入无界可变性。我们的监测框架的一个关键组成部分是一种新颖的高效算法,用于对密集时间信号进行滑动窗口聚合。
We investigate online monitoring algorithms over dense-time and continuous-time signals for properties written in metric temporal logic (MTL). We consider an abstract algebraic semantics based on complete lattices, which subsumes the Boolean (qualitative) semantics and the real-valued robustness (quantitative) semantics. Our semantics also extends to truth values that are partially ordered and allows the modeling of uncertainty in satisfaction. We propose a compositional approach for the construction of online monitors based on a class of infinite-state deterministic signal transducers that (1) are allowed to produce the output signal with some bounded delay relative to the input signal, and (2) do not introduce unbounded variability in the output signal. A key ingredient of our monitoring framework is a novel efficient algorithm for sliding-window aggregation over dense-time signals.
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发表时间: 2018-11-01
影响因子: 2.9
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