1. Fuzzy Logic Applied to System Monitors
- Author
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Lipika Deka, Miguel A. Molina-Cabello, David Elizondo, Noel Khan, [Khan, Noel] De Montfort Univ, Sch Comp Sci & Informat, Leicester LE1 9B1L, Leics, England, [Elizondo, David A.] De Montfort Univ, Sch Comp Sci & Informat, Leicester LE1 9B1L, Leics, England, [Deka, Lipika] De Montfort Univ, Sch Comp Sci & Informat, Leicester LE1 9B1L, Leics, England, [Molina-Cabello, Miguel A.] Univ Malaga, Dept Comp Languages & Comp Sci, Malaga 29071, Spain, [Molina-Cabello, Miguel A.] Inst Invest Biomed Malaga IBIMA, Malaga 29010, Spain, Ministry of Science, Innovation and Universities of Spain through the Project Automated Detection With Low-Cost Hardware of Unusual Activities in Video Sequences, Autonomous Government of Andalusia (Spain) through the Project Detection of Anomalous Behavior Agents by Deep Learning in Low-Cost Video Surveillance Intelligent Systems, European Regional Development Fund (ERDF), Universidad de Malaga, and Instituto de Investigacion Biomedica de Malaga (IBIMA)
- Subjects
Market research ,Fuzzy sets ,Monitoring ,General Computer Science ,Computer science ,Mission critical ,Fuzzy set ,02 engineering and technology ,Software reliability ,01 natural sciences ,Fuzzy logic ,0202 electrical engineering, electronic engineering, information engineering ,General Materials Science ,0101 mathematics ,Productivity ,business.industry ,010102 general mathematics ,Uncertainty ,General Engineering ,Fault tolerance ,Linguistics ,Usability ,Fuzzy systems ,Fuzzy control system ,software reliability ,Autonomous systems ,TK1-9971 ,Reliability engineering ,Variety (cybernetics) ,monitoring ,fuzzy systems ,020201 artificial intelligence & image processing ,fault tolerance ,Electrical engineering. Electronics. Nuclear engineering ,State (computer science) ,business - Abstract
The Publisher's final version can be found by following the DOI link. Open access article. System monitors are applications used to monitor other systems (often mission critical) and take corrective actions upon a system failure. Rather than reactively take action after a failure, the potential of fuzzy logic to anticipate and proactively take corrective actions is explored here. Failures adversely affect a system’s non-functional qualities (e.g., availability, reliability, and usability) and may result in a variety of losses such as data, productivity, or safety losses. The detection and prevention of failures necessarily improves a critical system’s non-functional qualities and avoids losses. The paper is self-contained and reviews set and logic theory, fuzzy inference systems (FIS), explores parameterization, and tests the neighborhood of rule thresholds to evaluate the potential for anticipating failures. Results demonstrate detectable gradients in FIS state spaces and means fuzzy logic based system monitors can anticipate rule violations or system failures.
- Published
- 2021