Determining Most Likely Links (MLL) for Network Fault Localization
We propose and evaluate a technique that learns the probability of a network transmission link experiencing a fault by using outlier flows (in the performance sense) as training data. This technique autonomously determines the most likely links causing performance degradation in a communications net...
Main Authors: | Christopher Mendoza, Michael P. McGarry |
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Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
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Series: | IEEE Open Journal of the Communications Society |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10044186/ |
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