Furcy Pin , ENS

Location :

at INRIA,  
meeting room « verte (green)  1 », 5th floor, 23 
avenue d'Italie, 75013 PARIS

Access: https://intranet.paris-rocquencourt.inria.fr/pratique/pre-antenne-parisienne/comment-se-rendre-a-la-pre-antenne-paris-italie/

Abstract :

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. We focus 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 time are estimated for  every node in the tree. The estimation is performed using Maximum 
Likelihood Estimator (MLE) and the Expectation-Maximization (EM) algorithm. Using queuing 
theory results, we 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 a 
non-discretized delays and a full MLE, EM is known to be slow. We hence present a yet very 
simple but, in our case, very effective speedup technique using Principal Component Analysis 
(PCA). MLE estimations are provided for a few different trees to evaluate our technique.

Host :

INRIA