Main navigation  Main content
Organizers:
Walter
Willinger
AT&T Labs  Research
walter@research.att.com
http://www.research.att.com/~walter/
and
John Doyle
California Institute of Technology
doyle@cds.caltech.edu
http://www.cds.caltech.edu/~doyle/home.htm
This tutorial uses the Internet as starting point for a scientific exploration of the broader issues of robustness in complex systems throughout technology and biology. In most of these systems, complexity is driven by the need for robustness to uncertainty in their environments and components far more than by basic functionality. At the same time, most of this complexity tends to be hidden, deliberately creating the illusion of superficially simple systems, which has encouraged the development of specious theories.
The objective of this tutorial is to outline an emerging theoretical foundation for the Internet that provides a sound framework for understanding both success and shortcomings of existing Internet technologies, offers alternative protocols for identified problems, guides the rational design for future evolution of ubiquitous networking, and suggests what new mathematics and technology will be needed for developing a useful, general theory of complex systems.


SUNDAY,
FEBRUARY 8 All talks are in Lecture Hall EE/CS 3180 unless otherwise noted. 


9:0010:00  John
Doyle California Institute of Technology 
Biology 101 for Networking Researcher: The Biological Internet I 
10:3011:30  John
Doyle California Institute of Technology 
Biology 101 for Networking Researcher: The Biological Internet II 
1:302:30  Stephen
Prajna California Institute of Technology 
Robustness in Complex Systems: Theoretical Foundations I 
3:004:00  Antonis
Papachristodoulou California Institute of Technology 
Robustness in Complex Systems: Theoretical Foundations II 
Abstracts
Antonis Papachristodoulou (California Institute of Technology) antonis@its.caltech.edu
Robustness in Complex Systems: Theoretical Foundations II
Ordinary or Functional differential equations with uncertain parameters can be used to model a variety of systems. Analysis usually proceeds by further simplification to the investigation of the linearizations of these models, or a series of assumptions that result in conservativeness or may be misleading. This methodology offers scalability, but the conclusions are only locally correct. Investigating the properties of the system at the nonlinear level with delays is usually cumbersome. Using the Sum of Squares decomposition, we will build a framework for the algorithmic analysis of nonlinear ordinary and functional differential equations, taking examples from network congestion control.
LIST OF CONFIRMED PARTICIPANTS
NAME  DEPARTMENT  AFFILIATION 

Scot Adams  Institute for Mathematics and its Applications  University of Minnesota, Twin Cities 
Soohan Ahn  Department of Statistics  Seoul National University 
David Alderson  Department of Computer Science  California Institute of Technology 
Greg Anderson  School of Mathematics  University of Minnesota, Twin Cities 
Douglas Arnold  Institute for Mathematics and its Applications  University of Minnesota, Twin Cities 
Donald Aronson  Institute for Mathematics and its Applications  University of Minnesota, Twin Cities 
Gerard Awanou  Institute for Mathematics and its Applications  University of Minnesota, Twin Cities 
Karen Ball  Institute for Mathematics and its Applications  University of Minnesota, Twin Cities 
Antar Bandyopadhyay  Institute for Mathematics and its Applications  University of Minnesota, Twin Cities 
Maury Bramson  School of Mathematics  University of Minnesota, Twin Cities 
Olga Brezhneva  Institute for Mathematics and its Applications  University of Minnesota, Twin Cities 
Hi Jun Choe  Department of Mathematics  Yonsei University 
Wanyang Dai  Department of Mathematics  Nanjing University 
John Doyle  Department of Control and Dynamical Systems  California Institute of Technology 
Philip Fleming  Network Advanced Technology  Motorola 
Shmuel Friedland  Department of Mathematics, Statistics, and Computer Science  University of Illinois, Chicago 
Tim Garoni  Institute for Mathematics and its Applications  University of Minnesota, Twin Cities 
Martin Greiner  Corporate Technology Department CT IC4  Siemens 
Tom Haigh  Adventium Labs  
ChuanHsiang Han  Institute for Mathematics and its Applications  University of Minnesota, Twin Cities 
Eric Harder  Office of Defense Computing Research  Department of Defense 
Naresh Jain  School of Mathematics  University of Minnesota, Twin Cities 
Ramesh Johari  Laboratory for Information and Decision Systems  Massachusetts Institute of Technology 
Lili Ju  Institute for Mathematics and its Applications  University of Minnesota, Twin Cities 
Herve Kerivin  Institute for Mathematics and its Applications  University of Minnesota, Twin Cities 
Mohammad Khan  Department of Mathematics  Kent State University 
Dohyun Kim  Department of Statistics  Seoul National University 
HyeRyoung Kim  Seoul National University  
Devdatta Kulkarni  University of Minnesota, Twin Cities  
Thomas Kurtz  Department of Mathematics  University of Wisconsin, Madison 
Lun Li  Department of Electrical Engineering  California Institute of Technology 
Zhuoqing Mao  Department of Electrical Engineering and Computer Science  University of Michigan 
Richard McGehee  School of Mathematics  University of Minnesota, Twin Cities 
Haewon Nam  Institute of Mathematics and Statistics  University of Minnesota, Twin Cities 
Amir Niknejad  Department of Mathematics  University of Illinois, Chicago 
Antonis Papachristodoulou  Department of Control and Dynamical Systems  California Institute of Technology 
Pablo Parrilo  Automatic Control Laboratory  Eidgenössische TH ZürichZentrum 
Lea Popovic  Institute for Mathematics and its Applications  University of Minnesota, Twin Cities 
Stephen Prajna  Department of Control and Dynamical Systems  California Institute of Technology 
Grzegorz Rempala  Department of Mathematics  University of Louisville 
Fadil Santosa  Institute for Mathematics and its Applications  University of Minnesota, Twin Cities 
Arnd Scheel  School of Mathematics  University of Minnesota, Twin Cities 
Tamon Stephen  Institute of Mathematics and its Application  University of Minnesota, Twin Cities 
Hui Wang  Division of Applied Mathematics  Brown University 
Jing Wang  Institute for Mathematics and its Applications  University of Minnesota, Twin Cities 
Walter Willinger  Statistics Research  AT&T Laboratories  Research 
Yuhong Yang  Department of Statistics  Iowa State University 
Ofer Zeitouni  School of Mathematics  University of Minnesota, Twin Cities 
Lixia Zhang  Department of Computer Science  University of California, Los Angeles 
Jun Zhao  Institute of Mathematics and its Application  University of Minnesota, Twin Cities 