Moore-Machine Filtering for Timed and Untimed Pattern Matching

TL;DR

This paper introduces a Moore-machine based filtering method for pattern matching in runtime verification, applicable to both timed and untimed automata, enhancing efficiency in embedded systems with limited resources.

Contribution

It presents a novel automata-theoretic construction of Moore machines serving as filters for pattern automata, suitable for real-time embedded applications.

Findings

The filtering method is sound, ensuring no matches are lost.

Experimental results show practical efficiency improvements.

Applicable to both timed and untimed automata.

Abstract

Monitoring is an important body of techniques in runtime verification of real-time, embedded, and cyber-physical systems. Mathematically, the monitoring problem can be formalized as a pattern matching problem against a pattern automaton. Motivated by the needs in embedded applications---especially the limited channel capacity between a sensor unit and a processor that monitors---we pursue the idea of filtering as preprocessing for monitoring. Technically, for a given pattern automaton, we present a construction of a Moore machine that works as a filter. The construction is automata-theoretic, and we find the use of Moore machines particularly suited for embedded applications, not only because their sequential operation is relatively cheap but also because they are amenable to hardware acceleration by dedicated circuits. We prove soundness (i.e., absence of lost matches), too. We work in two settings: in the untimed one, a pattern is an NFA; in the timed one, a pattern is a timed automaton. The extension of our untimed construction to the timed setting is technically involved, but our experiments demonstrate its practical benefits.