Diagnosis of Stochastic Discrete Event Systems Based on N-Gram Models with Wildcard Characters


IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E99-A   No.2   pp.462-467
Publication Date: 2016/02/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E99.A.462
Type of Manuscript: Special Section PAPER (Special Section on Mathematical Systems Science and its Applications)
discrete event systems,  diagnosis,  N-gram model,  wildcard character,  

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In previous papers by the authors, a new scheme for diagnosis of stochastic discrete event systems, called sequence profiling (SP), is proposed. From given event logs, N-gram models that approximate the behavior of the target system are extracted. N-gram models are used for discovering discrepancy between observed event logs and the behavior of the system in the normal situation. However, when the target system is a distributed system consisting of several subsystems, event sequences from subsystems may be interleaved, and SP cannot separate the faulty event sequence from the interleaved sequence. In this paper, we introduce wildcard characters into event patterns. This contributes to removing the effect by subsystems which may not be related to faults.