The statistical problem for network tomography is to infer the distribution of X, with mutually
independent components, from a measurement model Y= AX, where A is a given binary …

To facilitate the development of statistical methods geared at analyzing data from networks,
it is important to have metrics which define and measure distances between a network's …

Network tomography establishes linear relationships between the characteristics of
individual links and those of end-to-end paths. It has been proved that these relationships …

Network monitoring and diagnosis are key to improving network performance. The
difficulties of performance monitoring lie in today's fast growing Internet, accompanied by …

The modeling and analysis of computer communications networks give rise to a variety of
interesting statistical problems. This chapter focuses on network tomography, a term used to …

The origin-destination (OD) traffic matrix of a computer network is useful for solving problems
in design, routing, configuration debugging, monitoring, and pricing. Directly measuring this …

Providers of high quality-of-service over telecommunication networks require accurate
methods for remote measurement of link-level performance. Recent research in network …

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 …

The substantial overhead of performing internal network monitoring motivates techniques for
inferring spatially localized information about performance using only end-to-end …

Boolean Inference makes it possible to observe the congestion status of end-to-end paths
and infer, from that, the congestion status of individual network links. In principle, this can be …