Large-scale networks such as the Internet, with their tremendous growth, heterogeneity, and unpredictable or chaotic dynamics, are a gold mine for new, exciting and challenging mathematical problems, where scale, complexity, robustness, adaptivity, and dynamics play key roles and can no longer be ignored. Solving these problems can be expected to have profound implications for the efficient design and effective engineering, control, and management of future communication networks such as the next-generation Internet or networks of massively distributed, dynamic, and physically-embedded devices (e.g., sensor networks). The study of these networks relies more and more on an interdisciplinary approach that looks to other areas in the natural and social sciences where experimenting with and analyzing large-scale, complex, and highly interacting dynamical systems have a long tradition, e.g., biology, experimental physics, mathematical sciences, and economics.
This program lies on the interface of the mathematical/physical/biological sciences and computer/engineering science. Its goal is to initiate, facilitate and foster interactions among researchers of highly diverse backgrounds who pursue the common but ambitious goal of unraveling the ill-understood dynamics of large-scale complex networks. It is structured around three complementary emerging research topics that provide new and untested opportunities for “hands-on” workshops or activities consisting of a unique mixture of relevant experimental and theoretical research: next-generation network measurement infrastructures (based on the DARPA-funded National Internet Measurement Infrastructure), next-generation network simulators, and massively distributed self-organizing systems such as sensor networks
David Donoho
(Stanford University)
John Doyle
(California Institute of Technology)
Deborah Estrin
(UCLA)
Walter Willinger
(AT&T)
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