  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.
