Multicast-based inference of network-internal delay distributions
IEEE/ACM Transactions on Networking (TON)
Triple Jump Acceleration for the EM Algorithm
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Towards multihop available bandwidth estimation
ACM SIGMETRICS Performance Evaluation Review
Inverse problems in queueing theory and Internet probing
Queueing Systems: Theory and Applications
Maximum pseudo likelihood estimation in network tomography
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Unicast-based inference of network link delay distributions with finite mixture models
IEEE Transactions on Signal Processing
Inverse problems in bandwidth sharing networks
Proceedings of the 24th International Teletraffic Congress
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Tomography is one of the most promising techniques today to provide spatially localized information about internal network performance in a robust and scalable way. The key idea is to measure performance at the edge of the network, and to correlate these measurements to infer the internal network performance.This paper focuses on a specific delay tomographic problem on a multicast diffusion tree, where end-to-end delays are observed at every leaf of the tree, and mean sojourn times are estimated for every node in the tree. The estimation is performed using the Maximum Likelihood Estimator (MLE) and the Expectation-Maximization (EM) algorithm.Using queuing theory results, we carefully justify the model we use in the case of rare probing. We then give an explicit EM implementation in the case of i.i.d. exponential delays for a general tree. As we work with non-discretized delays and a full MLE, EM is known to be slow. We hence present a very simple but, in our case, very effective speed-up technique using Principal Component Analysis (PCA). MLE estimations are provided for a few different trees to evaluate our technique.