Statistics and Data Science Seminar
Professor Vijay Nair
University of Michigan
Statistical Inverse Problems in Network Tomography
Abstract: The term network tomography characterizes two classes of large-scale inverse
problems that arise in the modeling and analysis of computer and communications
networks. One class of problems deals with passive tomography where network
traffic data are collected at the nodes, and the goal is to reconstruct
origin-destination traffic patterns. The second one is active network tomography
where the goal is to recover link-level quality of service parameters, such as
packet loss rates and delay distributions, from end-to-end path-level
measurements. Internet service providers use this to characterize network
performance and to monitor service quality. This talk will provide an overview
of the network application, the statistical inverse problems that arise, and
some recent research in trying to address them with an emphasis on active
tomography. This is joint work with George Michailidis, Earl Lawrence, Bowei Xi,
and Xiaodong Yang.
Wednesday April 25, 2007 at 3:30 PM in SEO 712