In modern business, educational, and other settings, it is common to provide a digital network that interconnects hardware devices for shared access by users (e.g., in an office where printers are available for use by all the office workers). In such a context, so-called soft failures, where a device silently starts working in a degraded mode, may easily go un-notices for a long time, resulting in potential productivity loss. It is therefore advantageous to enable system administrators to identify soft failures at an early stage. We propose to mine print logs in order to discover statistically significant deviations in the usage behavior of the overall infrastructure, and we identify such deviations with soft failures, or, in any case, situations of interest to an administrator.
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Soft failure detection using factorial hidden Markov models