Presentation + Paper
22 April 2020 The network link outlier factor (NLOF)
Author Affiliations +
Abstract
We present and evaluate the performance of our Network Link Outlier Factor (NLOF) for detecting transmission channel faults in communication networks. An NLOF is computed for each transmission channel in a network under management using the throughput values derived from ow data. Throughput values of flows are clustered in two stages, outlier values are determined within each of the clusters, and then ow outlier ratios determine the outlier score for each transmission channel (link). Specifically, we first cluster the throughput of flows into the set of clusters we believe will naturally exist in a network and then identify the outliers within those throughput clusters. Our technique to detect network transmission channel faults consists of: 1) ow throughput clustering, 2) ow throughput outlier detection using an outlier score, 3) tracing flows on the network topology using routing information, and 4) network link outlier score computation from ow outlier scores.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christopher Mendoza, Venkat Dasari, and Michael P. McGarry "The network link outlier factor (NLOF)", Proc. SPIE 11419, Disruptive Technologies in Information Sciences IV, 114190O (22 April 2020); https://doi.org/10.1117/12.2558716
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Analytics

Machine learning

Data modeling

Analytical research

Artificial intelligence

Autoregressive models

Computer networks

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