Discovering users with similar internet access performance through cluster analysis

作者：

Highlights：

• A new methodology to analyze Internet access behavior using frequency histograms.

• A two-level clustering approach to analyze real network measurements with noisy data.

• A new distance measure to identify user histogram outliers.

• Data mining support for distributed Internet monitoring applications.

摘要

•A new methodology to analyze Internet access behavior using frequency histograms.•A two-level clustering approach to analyze real network measurements with noisy data.•A new distance measure to identify user histogram outliers.•Data mining support for distributed Internet monitoring applications.

论文关键词：Cluster analysis,Internet access performance,Anomaly detection,Network monitoring

论文评审过程：Received 29 March 2016, Revised 1 July 2016, Accepted 3 August 2016, Available online 4 August 2016, Version of Record 10 August 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.08.025