Pattern Matching in Link Streams: Timed-Automata with Finite Memory

Abstract : Link streams model the dynamics of interactions in complex distributed systems as sequences of links (interactions) occurring at a given time. Detecting patterns in such sequences is crucial for many applications but it raises several challenges. In particular, there is no generic approach for the specification and detection of link stream patterns in a way similar to regular expressions and automata for text patterns. To address this, we propose a novel automata framework integrating both timed constraints and finite memory together with a recognition algorithm. The algorithm uses structures similar to tokens in high-level Petri nets and includes non-determinism and concurrency. We illustrate the use of our framework in real-world cases and evaluate its practical performances.
Complete list of metadatas

Cited literature [24 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-02110475
Contributor : Lionel Tabourier <>
Submitted on : Thursday, April 25, 2019 - 2:00:05 PM
Last modification on : Monday, October 28, 2019 - 10:50:22 AM

File

SACS.pdf
Files produced by the author(s)

Identifiers

Citation

Clément Bertrand, Frédéric Peschanski, Hanna Klaudel, Matthieu Latapy. Pattern Matching in Link Streams: Timed-Automata with Finite Memory. Scientific Annals of Computer Science, 2018, 28 (36), pp.161-198. ⟨10.7561/SACS.2018.2.161⟩. ⟨hal-02110475⟩

Share

Metrics

Record views

57

Files downloads

66