%0 Magazine Article
%D 2004
%T Network tomography: recent developments pp. 499-517.
%A Rui Castro
%A M. J. Coates
%A Robert D. Nowak
%A Bin Yu
%K Network tomography
%K pseudo-likelihood
%K topology identiﬁcation
%K tree estimation
%N 3
%P 499-517
%V 19
%X Today’s Internet is a massive, distributed network which continues to explode in size as e-commerce and related activities grow. The heterogeneous and largely unregulated structure of the Internet renders tasks such as dynamic routing, optimized service provision, service level veriﬁcation and detection of anomalous/malicious behavior extremely challenging. The problem is compounded by the fact that one cannot rely on the cooperation of individual servers and routers to aid in the collection of network trafﬁc measurements vital for these tasks. In many ways, network monitoring and inference problems bear a strong resemblance to other “inverse problems” in which key aspects of a system are not directly observable. Familiar signal processing or statistical problems such as tomographic image reconstruction and phylogenetic tree identiﬁcation have interesting connections to those arising in networking. This article introduces network tomography, a new ﬁeld which we believe will beneﬁt greatly from the wealth of statistical theory and algorithms. It focuses especially on recent developments in the ﬁeld including the application of pseudo-likelihood methods and tree estimation formulations.
%8 08/2004
%> http://networks.ece.mcgill.ca/sites/default/files/castro_StatSciMagazine04.pdf