Network tomography on general topologies
SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
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Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
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IEEE/ACM Transactions on Networking (TON)
Moment estimation in delay tomography with spatial dependence
Performance Evaluation
Algebra-based scalable overlay network monitoring: algorithms, evaluation, and applications
IEEE/ACM Transactions on Networking (TON)
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IEEE/ACM Transactions on Networking (TON)
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ICC'09 Proceedings of the 2009 IEEE international conference on Communications
On the scalability of RTCP-based network tomography for IPTV services
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Network tomography using multicast probes enables inference of loss characteristics of internal network links from reports of end-to-end loss seen at multicast receivers. We develop estimators for internal loss rates when reports are not available on all probes or from all receivers. This problem is motivated by the use of unreliable transport protocols, such as reliable transport protocol, to transmit loss reports to a collector for inference. We use a maximum-likelihood (ML) approach in which we apply the expectation maximization (EM) algorithm to provide an approximating solution to the the ML estimator for the incomplete data problem. We present a concrete realization of the algorithm that can be applied to measured data. For classes of models, we establish identifiability of the probe and report loss parameters, and convergence of the EM sequence to the maximum-likelihood estimator (MLE). Numerical results suggest that these properties hold more generally. We derive convergence rates for the EM iterates, and the estimation error of the MLE. Finally, we evaluate the accuracy and convergence rate through extensive simulations