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

被引：4

作者：

Baralis, Elena ^{[1
]}

Bianco, Andrea ^{[2
]}

Cerquitelli, Tania ^{[1
]}

Chiaraviglio, Luca ^{[3
]}

Mellia, Marco ^{[2
]}

机构：

[1] Politecn Torino, Dipartimento Automat & Informat, Turin, Italy

[2] Politecn Torino, Dipartimento Elettron & Telecomunicaz, Turin, Italy

[3] Univ Nice Sophia, CNRS, Mascotte, INRIA,I3S, Sophia Antipolis, France

来源：

COMPUTER NETWORKS | 2013年 / 57卷 / 17期

关键词：

Clustering algorithms; Data analytics; Internet measurements and characterization; ALGORITHM;

D O I：

10.1016/j.comnet.2013.07.019

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：3300 / 3315

页数：16

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