Diagnosis of Stochastic Discrete Event Systems Based on N-Gram Models with Wildcard Characters
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E99-A No.2 pp.462-467
- Publication Date
- 2016/02/01
- Publicized
- 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)
- Category
Authors
Kunihiko HIRAISHI
Japan Advanced Institute of Science and Technology
Koichi KOBAYASHI
Japan Advanced Institute of Science and Technology
Keyword
Latest Issue
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Kunihiko HIRAISHI, Koichi KOBAYASHI, "Diagnosis of Stochastic Discrete Event Systems Based on N-Gram Models with Wildcard Characters" in IEICE TRANSACTIONS on Fundamentals,
vol. E99-A, no. 2, pp. 462-467, February 2016, doi: 10.1587/transfun.E99.A.462.
Abstract: 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.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E99.A.462/_p
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@ARTICLE{e99-a_2_462,
author={Kunihiko HIRAISHI, Koichi KOBAYASHI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Diagnosis of Stochastic Discrete Event Systems Based on N-Gram Models with Wildcard Characters},
year={2016},
volume={E99-A},
number={2},
pages={462-467},
abstract={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.},
keywords={},
doi={10.1587/transfun.E99.A.462},
ISSN={1745-1337},
month={February},}
Copy
TY - JOUR
TI - Diagnosis of Stochastic Discrete Event Systems Based on N-Gram Models with Wildcard Characters
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 462
EP - 467
AU - Kunihiko HIRAISHI
AU - Koichi KOBAYASHI
PY - 2016
DO - 10.1587/transfun.E99.A.462
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E99-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 2016
AB - 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.
ER -
English
