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Complex Systems Program
This page is not currently being maintained and is for archival information only.
Please see our most recent work at: Measurement Science for Complex Information Systems
Complex Systems are composed of large interrelated, interacting entities which taken together, exhibit a macroscopic behavior which is not predictable by examination of the individual entities. The Complex Systems Program seeks to understand the fundamental science of these systems and develop rigorous descriptions (analytic, statistical, or semantic) that enable prediction and control of their behavior. Initially focused on the Internet and Grid Computing, this Program will facilitate predictability and reliability in these areas and other complex systems such as biotechnology, nanotechnology, semiconductors, and complex engineering.
Programs/Projects:
- Complex Systems Fundamentals
Roldan Pozo - Measurement Science for Complex Information Systems
Kevin Mills, Chris Dabrowski, Vladimir Marbukh, Jim Filliben, Fern Hunt, Dan Genin, Dennis Leber - Complex Systems Testbed
Vince Stanford, Lukas Diduch, Imad Hamchi, Mathieu Hoarau, Antoine Fillinger - Methods for Characterizing Complex Networks
Isabel Beichl, Brian Cloteaux
Latest Publications:
- Using Markov Chain Analysis to Study Dynamic Behavior in Large-Scale Grid Systems
Dabrowski, Hunt - Dynamic Routing and Congestion Control Through Random Assignment of Routes
Hunt, Marbukh - Measuring the Effectiveness of the s-Metric to Produce Better Network Models
Beichl, Cloteaux
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Contacts
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(301) 975-2982