Explicit loss inference in multicast tomography Academic Article

abstract

• Network performance tomography involves correlating end-to-end performance measures over different network paths to infer the performance characteristics on their intersection. Multicast based inference of link-loss rates is the first paradigm for the approach. Existing algorithms generally require numerical solution of polynomial equations for a maximum-likelihood estimator (MLE), or iteration when applying the expectation maximization (EM) algorithm. The purpose of this note is to demonstrate a new estimator for link-loss rates that is computationally simple, being an explicit function of the measurements, and that has the same asymptotic variance as the MLE, to first order in the link-loss rates. 2006 IEEE.

authors

• Duffield, Nick

published proceedings

• IEEE TRANSACTIONS ON INFORMATION THEORY

author list (cited authors)

• Duffield, N. G., Horowitz, J., Lo Presti, F., & Towsley, D.

citation count

• 14

complete list of authors

• Duffield, Nicholas G||Horowitz, Joseph||Lo Presti, Francesco||Towsley, Don

publication date

• August 2006

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE TRANSACTIONS ON INFORMATION THEORY  Journal

keywords

• End-to-end Measurement
• Link-loss Rates
• Statistical Inference

Digital Object Identifier (DOI)

• 10.1109/TIT.2006.878228

start page

• 3852

end page

• 3855

volume

• 52

issue

• 8