A flexible model for resource management in virtual private networks
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
MPLS: technology and applications
MPLS: technology and applications
Traffic matrix estimation: existing techniques and new directions
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Fast accurate computation of large-scale IP traffic matrices from link loads
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Performance of estimated traffic matrices in traffic engineering
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
An information-theoretic approach to traffic matrix estimation
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Traffic engineering with estimated traffic matrices
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Traffic matrix estimation on a large IP backbone: a comparison on real data
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
Measurement based characterization and provisioning of IP VPNs
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
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We address the problem of estimating the source-destination (SD) traffic matrix of a VPN from measurements of aggregated traffic along all access links. We derive two different estimators by formulating the estimation of the SD-traffic matrix in the form of both deterministic and stochastic optimization problems. One estimator yields the estimates from a snapshot of the access link loads; the other yields estimates from a set of measurements of the access link loads by using a statistical method. The proposed estimators have expressions much simpler than those of the standard SD-traffic-matrix estimators; one estimator has an explicit representation that does not involve matrix inversion. The other estimator is given by a simple matrix formula and does not need any prior SD-traffic matrices. Through simulation experiments, we show that these proposals are superior or comparable to the standard SD-traffic-matrix estimator in term of estimation accuracy.