A Compositional Framework for Quantitative Online Monitoring over Continuous-time Signals
Konstantinos Mamouras, Agnishom Chattopadhyay and Zhifu Wang
Abstract: 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.