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학술대회 Design of the Autonomous Fault Manager for Learning and Estimating Home Network Faults
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International Conference on Consumer Electronics (ICCE) 2009, pp.1-2
08MC1900, 고신뢰성 유비쿼터스홈 적응형 미들웨어 개발, 문경덕
This paper proposes a design of software Autonomous Fault Manager (AFM) for learning and estimating faults generated in home network. Most of the existing researches employ rule-based fault processing mechanism, but those works depend on the static characteristics of rules for a specific home environment. Therefore, we focus on a fault estimating and learning mechanism that autonomously produces a fault diagnosis rule and predicts an expected fault pattern in the mutually different home environment. For this, the proposed AFM extracts the home network information with a set of training data using the 5W1H (Who, What, When, Where, Why, How) based contexts to autonomously produce a new fault diagnosis rule. The fault pattern with high correlations can then be predicted for the current home network operation pattern. ©2009 IEEE.
KSP 제안 키워드
Diagnosis Rule, Fault processing, Home Network, Home environment, Network information, Operation pattern, Processing mechanism, Rule-based, fault diagnosis, fault pattern, learning mechanism