On inferring autonomous system relationships in the internet
IEEE/ACM Transactions on Networking (TON)
Traffic matrix estimation: existing techniques and new directions
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Towards capturing representative AS-level Internet topologies
Computer Networks: The International Journal of Computer and Telecommunications Networking
Structural analysis of network traffic flows
Proceedings of the joint international conference on Measurement and modeling of computer systems
Diagnosing network-wide traffic anomalies
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
A methodology for estimating interdomain web traffic demand
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
Simplifying the synthesis of internet traffic matrices
ACM SIGCOMM Computer Communication Review
IEEE/ACM Transactions on Networking (TON)
An independent-connection model for traffic matrices
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
AS relationships: inference and validation
ACM SIGCOMM Computer Communication Review
An empirical approach to modeling inter-AS traffic matrices
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Spatio-temporal compressive sensing and internet traffic matrices
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Exact Matrix Completion via Convex Optimization
Foundations of Computational Mathematics
Matrix completion from a few entries
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1
A Singular Value Thresholding Algorithm for Matrix Completion
SIAM Journal on Optimization
Proceedings of the 6th International COnference
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The ability of an ISP to infer traffic volumes that are not directly measurable can be useful for research, engineering, and business intelligence. Previous work has shown that traffic matrix completion is possible, but there is as yet no clear understanding of which ASes are likely to be able to perform TM completion, and which traffic flows can be inferred. In this paper we investigate the relationship between the AS-level topology of the Internet and the ability of an individual AS to perform traffic matrix completion. We take a three-stage approach, starting from abstract analysis on idealized topologies, and then adding realistic routing and topologies, and finally incorporating realistic traffic on which we perform actual TM completion. Our first set of results identifies which ASes are best-positioned to perform TM completion. We show, surprisingly, that for TM completion it does not help for an AS to have many peering links. Rather, the most important factor enabling an AS to perform TM completion is the number of direct customers it has. Our second set of results focuses on which flows can be inferred. We show that topologically close flows are easier to infer, and that flows passing through customers are particularly well suited for inference.