NetCluster: A clustering-based framework to analyze internet passive measurements data

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• 作者：Elena Baralis ; Andrea Bianco ; Tania Cerquitelli ; Luca Chiaraviglio ; Marco Mellia
• 关键词：Clustering algorithms ; Data analytics ; Internet measurements and characterization
• 刊名：Computer Networks
• 出版年：9 December, 2013
• 年：2013
• 卷：57
• 期：17
• 页码：3300-3315
• 全文大小：1354 K

文摘

Internet measured data collected via passive measurement are analyzed to obtain localization information on nodes by clustering (i.e., grouping together) nodes that exhibit similar network path properties. Since traditional clustering algorithms fail to correctly identify clusters of homogeneous nodes, we propose the NetCluster novel framework, suited to analyze Internet measurement datasets. We show that the proposed framework correctly analyzes synthetically generated traces. Finally, we apply it to real traces collected at the access link of Politecnico di Torino campus LAN and discuss the network characteristics as seen at the vantage point.