Detail výsledku

EvoParser: An Evolutionary Approach to Log Parsing

SETINSKÝ, J.; ŽÁDNÍK, M. EvoParser: An Evolutionary Approach to Log Parsing. In 38th IEEE/IFIP Network Operations and Management Symposium, NOMS 2025. Honolulu: IEEE Communications Society, 2025. p. 1-8. ISBN: 979-8-3315-3164-5.
Typ
článek ve sborníku konference
Jazyk
angličtina
Autoři
Abstrakt

In the domain of network operations and manage-ment, efficient log parsing is crucial for processing the highvolumes of log data necessary to monitor the reliability andperformance of the operated infrastructures and services. Thispaper introduces a novel method for creating highly efficientlog parsers. Our method employs a genetic algorithm to evolveoptimized log parsing graphs that deliver high-quality parsingresults. Experimental evaluations demonstrate that our approach achieves results comparable to or better than state-of-the-art techniques while maintaining low complexity during parsing.These characteristics make it particularly suitable for real-timeapplications in high-volume data scenarios.

Rok
2025
Strany
1–8
Sborník
38th IEEE/IFIP Network Operations and Management Symposium, NOMS 2025
Konference
IEEE/IFIP Network Operations and Management Symposium 2025
ISBN
979-8-3315-3164-5
Vydavatel
IEEE Communications Society
Místo
Honolulu
DOI
UT WoS
001556086900129
EID Scopus
BibTeX
@inproceedings{BUT193350,
  author="Jiří {Setinský} and Martin {Žádník}",
  title="EvoParser: An Evolutionary Approach to Log Parsing",
  booktitle="38th IEEE/IFIP Network Operations and Management Symposium, NOMS 2025",
  year="2025",
  pages="1--8",
  publisher="IEEE Communications Society",
  address="Honolulu",
  doi="10.1109/NOMS57970.2025.11073703",
  isbn="979-8-3315-3164-5"
}
Projekty
Application-specific HW/SW architectures and their applications, VUT, Vnitřní projekty VUT, FIT-S-23-8141, zahájení: 2023-03-01, ukončení: 2026-02-28, řešení
Pracoviště
Nahoru