Bineet Ghosh ; Étienne André - Offline and online energy-efficient monitoring of scattered uncertain logs using a bounding model

lmcs:10434 - Logical Methods in Computer Science, January 11, 2024, Volume 20, Issue 1 - https://doi.org/10.46298/lmcs-20(1:2)2024
Offline and online energy-efficient monitoring of scattered uncertain logs using a bounding modelArticle

Authors: Bineet Ghosh ; Étienne André

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.


Volume: Volume 20, Issue 1
Secondary volumes: Selected Papers of the 42nd International Conference on Formal Techniques for Distributed Objects, Components and Systems (FORTE 2022)
Published on: January 11, 2024
Accepted on: October 23, 2023
Submitted on: December 7, 2022
Keywords: Electrical Engineering and Systems Science - Systems and Control, Computer Science - Software Engineering
Funding:
    Source : OpenAIRE Graph
  • Better Synthesis for Underspecified Quantitative Systems; Funder: French National Research Agency (ANR); Code: ANR-22-CE48-0012
  • CPS: Medium: GOALI: Design Automation for Automotive Cyber-Physical Systems; Funder: National Science Foundation; Code: 2038960
  • Provable Mitigation of Side Channel through Parametric Verification; Funder: French National Research Agency (ANR); Code: ANR-19-CE25-0015

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References
Ghosh, B. ORCID, & André, É. (2023). MoULDyS: Monitoring of autonomous systems in the presence of uncertainties. In Science of Computer Programming (Vols. 230, p. 102976). Elsevier BV. 10.1016/j.scico.2023.102976

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