Probability
and Statistics in Complex Systems: Genomics, Networks, and Financial
Engineering, September 1, 2003 - June 30, 2004
Abstracts:
IMA
Tutorial:
January
11, 2004

Paul
Barford (Department of Computer Sciences, University
of Wisconsin-Madison) pb@cs.wisc.edu
Measurement,
Modeling and Analysis of the Internet
There are many reasons for taking measurements in the Internet;
from serving as a basis for scientific study to performing
day to day operational management tasks. While taking measurements
in the Internet can be as simple as running "pings" from a
single desktop system, systematic large scale measurements
are fraught with difficulty. In this tutorial we will describe
the standard tools and techniques for taking measurements
of a variety of Internet features and behaviors. We will also
present the major infrastructures that have been deployed
recently (and not so recently) for taking large scale measurements
of the Internet. These infrastructures are principally used
to gather data on Internet topology, routing, and traffic
behavior. We will follow this with an overview of the standard
techniques for organizing and analyzing Internet measurement
data. We will conclude with a discussion of the many challenges
facing researchers who wish to conduct Internet measurement
studies or to use data gathered in Internet
measurement infrastructures.

Vishal
Misra (Department of Computer Science, Columbia University
in the City of New York) misra@cs.columbia.edu http://www.cs.columbia.edu/~misra
Measurement,
Modeling, and Analysis of the Internet: Part II
In this tutorial we will cover some of the important developments
in the mathematical modeling and analysis of aspects of the
Internet. We will be focusing on three areas (i) There has been
a great deal of interest in the "self-similar," "fractal," or
more appropriately long range dependent (LRD) nature of Internet
traffic. We will introduce various models that have attempted
to explain the LRD phenomena (ii) Measurements of the Internet
topology have led to a number of modeling efforts to understand
and explain the power law nature of the connectivity graph.
We will look at some of the well known models (iii) TCP carries
upwards of 90% of Internet traffic. Modeling TCP specifically,
and congestion control on the Internet in general, has been
a hot area of networking research in the past few years. We
will outline the important and well known efforts in the area
in the tutorial.

Probability
and Statistics in Complex Systems: Genomics, Networks, and Financial
Engineering, September 1, 2003 - June 30, 2004