Article Dans Une Revue Logical Methods in Computer Science Année : 2024

Offline and online energy-efficient monitoring of scattered uncertain logs using a bounding model

Résumé

Monitoring the correctness of distributed cyber-physical systems is essential. Detecting possible safety violations can be hard when some samples are uncertain or missing. We monitor here black-box cyber-physical system, with logs being uncertain both in the state and timestamp dimensions: that is, not only the logged value is known with some uncertainty, but the time at which the log was made is uncertain too. In addition, we make use of an over-approximated yet expressive model, given by a non-linear extension of dynamical systems. Given an offline log, our approach is able to monitor the log against safety specifications with a limited number of false alarms. As a second contribution, we show that our approach can be used online to minimize the number of sample triggers, with the aim at energetic efficiency. We apply our approach to three benchmarks, an anesthesia model, an adaptive cruise controller and an aircraft orbiting system.

Fichier principal
Vignette du fichier
2204.11505.pdf (1.06 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte
Licence
DOI

Cite 10.5281/zenodo.7888501 Ouvrage Ghosh, B., & André, É. (2023). MoULDyS: Monitoring of Autonomous Systems in the Presence of Uncertainties (Version v1.1). Zenodo. https://doi.org/10.5281/ZENODO.7888501

Dates et versions

hal-04654243 , version 1 (20-03-2025)

Licence

Identifiants

Citer

Bineet Ghosh, Étienne André. Offline and online energy-efficient monitoring of scattered uncertain logs using a bounding model. Logical Methods in Computer Science, 2024, Volume 20, Issue 1, ⟨10.46298/lmcs-20(1:2)2024⟩. ⟨hal-04654243⟩
182 Consultations
118 Téléchargements

Altmetric

Partager

  • More