Abstract
In discrete-event system monitoring, the observation is fragmented over time and a set of candidate diagnoses is output at the reception of each fragment (so as to allow for possible control and recovery actions). When the observation is uncertain (typically, a DAG with partial temporal ordering) a problem arises about the significance of the monitoring output: two sets of diagnoses, relevant to two consecutive observation fragments, may be unrelated to one another, and, even worse, they may be unrelated to the actual diagnosis. To cope with this problem, the notion of monotonic monitoring is introduced, which is supported by specific constraints on the fragmentation of the uncertain temporal observation, leading to the notion of stratification. The paper shows that only under stratified observations can significant monitoring results be guaranteed.
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Lamperti, G., Zanella, M. (2009). Monotonic Monitoring of Discrete-Event Systems with Uncertain Temporal Observations. In: Filipe, J., Cordeiro, J. (eds) Enterprise Information Systems. ICEIS 2009. Lecture Notes in Business Information Processing, vol 24. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01347-8_30
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DOI: https://doi.org/10.1007/978-3-642-01347-8_30
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