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Monitoring the correctness of distributed cyber-physical systems isessential. Detecting possible safety violations can be hard when some samplesare uncertain or missing. We monitor here black-box cyber-physical system, withlogs being uncertain both in the state and timestamp dimensions: that is, notonly the logged value is known with some uncertainty, but the time at which thelog was made is uncertain too. In addition, we make use of an over-approximatedyet expressive model, given by a non-linear extension of dynamical systems.Given an offline log, our approach is able to monitor the log against safetyspecifications 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 sampletriggers, with the aim at energetic efficiency. We apply our approach to threebenchmarks, an anesthesia model, an adaptive cruise controller and an aircraftorbiting system.

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