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- W2912152934 abstract "In an Ethernet network, a common type of failure is the temporary or extended loss of bandwidth, or soft failure as it is referred to in the literature. Though the causes of soft failures vary, to the network user such failures are perceived as noticeably degraded or anomalous performance.This research uses anomaly detection as a means to signal to performance degradations that are indicative of network faults. In addition, a paradigm called the fault feature vector is used to describe the anomalous conditions particular to a fault. This paradigm can be used to detect instances of specific faults by determining when anomalous conditions in the network match the feature vector description. In a two-year study of the CMU Computer Science Network the fault feature vector mechanism proved effective in detecting failures and discriminating between failure types. This mechanism was also effective at abstracting large amounts of network data to only those events which warrant operator attention; in this two-year study, over 32 million monitored data points were reduced to under a two hundred event matchings. The thesis closes with a discussion of potential uses of anomaly detection in network fault management." @default.
- W2912152934 created "2019-02-21" @default.
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- W2912152934 date "1992-01-01" @default.
- W2912152934 modified "2023-09-24" @default.
- W2912152934 title "Fault detection in an Ethernet network via anomaly detectors" @default.
- W2912152934 hasPublicationYear "1992" @default.
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