Evidence for long-tailed distributions in the internet
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Analyzing peer-to-peer traffic across large networks
IEEE/ACM Transactions on Networking (TON)
A methodology for estimating interdomain web traffic demand
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
The problem of synthetically generating IP traffic matrices: initial recommendations
ACM SIGCOMM Computer Communication Review
Providing public intradomain traffic matrices to the research community
ACM SIGCOMM Computer Communication Review
An independent-connection model for traffic matrices
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
An empirical approach to modeling inter-AS traffic matrices
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Spatio-temporal compressive sensing and internet traffic matrices
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Proceedings of the ACM SIGCOMM 2010 conference
Proceedings of the 6th International COnference
Dynamics of prefix usage at an edge router
PAM'11 Proceedings of the 12th international conference on Passive and active measurement
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Identifying the statistical properties of the Interdomain Traffic Matrix (ITM) is fundamental for Internet techno-economic studies but challenging due to the lack of adequate traffic data. In this work, we utilize a Europe-wide measurement infrastructure deployed at the GÉANT backbone network to examine some important spatial properties of the ITM. In particular, we analyze its sparsity and characterize the distribution of traffic generated by different ASes. Our study reveals that the ITM is sparse and that the traffic sent by an AS can be modeled as the LogNormal or Pareto distribution, depending on whether the corresponding traffic experiences congestion or not. Finally, we show that there exist significant correlations between different ASes mostly due to relatively few highly popular prefixes.