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

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 s...

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Bibliographic Details
Published inScientific annals of computer science Vol. 28; no. 2; pp. 161 - 198
Main Authors Bertrand, Clément, Peschanski, Frédéric, Klaudel, Hanna, Latapy, Matthieu
Format Journal Article
LanguageEnglish
Published Iasi Alexandru Ioan Cuza University of Iasi 25.09.2018
Alexandru Ioan Cuza University Publishing House
Subjects
Algorithms
Computer networks
Computer Science
Concurrency
Pattern matching
Pattern recognition
Petri nets
Social and Information Networks
Streams
finite-memory automata
complex networks
timed automata
difference bound matrices
Timed pattern recognition
link streams
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Summary: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.
ISSN:1843-8121
2248-2695
DOI:10.7561/SACS.2018.2.161