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
    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
    • CPS: Medium: GOALI: Design Automation for Automotive Cyber-Physical Systems; Funder: National Science Foundation; Code: 2038960
    • Better Synthesis for Underspecified Quantitative Systems; Funder: French National Research Agency (ANR); Code: ANR-22-CE48-0012
    • 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, Étienne. (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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