Toronto Networking
Seminar
Multiscale network monitoring and anomaly detection
Mark Coates
Department
of Electrical and Computer Engineering
McGill
University
Date:
Friday, November 9, 2:10pm
Location: BA1220 (Bahen Center)
Abstract:
Network operators need to monitor the end-to-end performance
experienced by all users in order to identify and correct for
overloaded links and to verify that quality of service agreements are
being satisfied. The key challenge is to obtain end-to-end
performance levels without the costly overhead involved in explicitly
gathering data for the paths connecting every source-destination
pair. Recently we proposed a method for characterizing
end-to-end performance across a network given limited
measurements. Our method uses diffusion wavelets, a
methodology for defining multi-scale representations of functions
defined on a graph, to obtain an efficient representation for network
performance parameters. With this representation, we can employ
nonlinear sparse estimation techniques, yielding a state-of-the-art
framework for network inference. This talk will describe this
monitoring framework, and discuss its application to network anomaly
detection and traffic matrix estimation.
Bio:
Mark Coates received a B.E. (first class honors) in computer systems
engineering from the University of Adelaide, Australia in 1995 and a
Ph.D. in information engineering from the University of Cambridge, U.K.
in 1999. Currently, he is an Assistant Professor at McGill University,
Montreal, Canada. He was awarded the Texas Instruments Postdoctoral
Fellowship in 1999 and was a research associate and lecturer at Rice
University, Texas, from 1999-2001. His research interests include
communication and sensor/actuator networks, statistical signal
processing, causal analysis, and Bayesian and Monte
Carlo inference.
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