ITR - (ASE+NHS) - (SIM+SOC): Characterizing the Dynamics of Complex Networks

Northeastern University, Boston MA

Investigators

Abstract

This award supports theoretical and computational research and education and is made on a proposal submitted to the Division of Materials Research under the Information Technology Research solicitation NSF-04-012. Research activities covered by this award fall under the National Priority Area, "Advances in Science and Engineering," and the Technical Focus Area, "Innovation in Computational Modeling or Simulation in Research." It may also contribute to the National Priority Area, "National Homeland Security" and the Technical Focus Area, "Interactions and Complex Interdependencies of Information Systems and Societal Systems." The complex interdependencies characterizing natural, informational and communication systems not only impact all aspects of human activity, but offer a series of novel challenges for contemporary science. The increasing evidence that complex networks are shaped by quantifiable organizing principles has generated interest in all research fields where networks play a role, from statistical mechanics to computer science and biology. Yet, to fully understand the impact of interconnectivity, it must be recognized that each network has a purpose, facilitating material or information transfer between the nodes. These processes assign to each node and link a dynamical variable characterizing their time-dependent activity and force us to view networks as dynamical systems. While the understanding of network topology has significantly improved in the past four years, the characterization of network dynamics and transport is still in its infancy. The goal of the present award is to develop an integrated research program addressing the dynamical implications of networks in various complex technological, natural and social systems. The interplay between network topology, dynamics and function will be investigated through a series of extensive measurements, recording for several communication and social networks the detailed time-dependent activity at each node and link. Building on these multi-channel measurements, the research program will explore the basic mechanisms that govern the dynamics of complex networks; study the development of localized high activity regions or "hot spots"; explore the dynamical correlations between the system's components and study the impact of groups and communities on network dynamics; address the dynamic vulnerabilities of complex networks, studying various topological and dynamical avenues to limit the impact of component failures. Finally, a series of models and analytical methods will be developed, aiming to turn the empirical results into predictive tools. The research program will involve the participation of postdoctoral associates, graduate students and undergraduate students. Educational activities will be further integrated with research activities by conducting an intensive weeklong summer school for undergraduate and graduate students on the fundamental aspects and applications o network theory. Also, a series of web-based lecture notes will be developed, designed to be used both in specialized network courses and as modules in existing physics, computer science or biology courses that require network analysis. %%% This award supports theoretical and computational research and education and is made on a proposal submitted to the Division of Materials Research under the Information Technology Research solicitation NSF-04-012. Research activities covered by this award fall under the National Priority Area, "Advances in Science and Engineering," and the Technical Focus Area, "Innovation in Computational Modeling or Simulation in Research." It may also contribute to the National Priority Area, "National Homeland Security" and the Technical Focus Area, "Interactions and Complex Interdependencies of Information Systems and Societal Systems." The complex interdependencies characterizing natural, informational and communication systems not only impact all aspects of human activity, but offer a series of novel challenges for contemporary science. The increasing evidence that complex networks are shaped by quantifiable organizing principles has generated interest in all research fields where networks play a role, from statistical mechanics to computer science and biology. Yet, to fully understand the impact of interconnectivity, it must be recognized that each network has a purpose, facilitating material or information transfer between the nodes. These processes assign to each node and link a dynamical variable characterizing their time-dependent activity and force us to view networks as dynamical systems. While the understanding of network topology has significantly improved in the past four years, the characterization of network dynamics and transport is still in its infancy. The goal of the present award is to develop an integrated research program addressing the dynamical implications of networks in various complex technological, natural and social systems. The interplay between network topology, dynamics and function will be investigated through a series of extensive measurements, recording for several communication and social networks the detailed time-dependent activity at each node and link. Building on these multi-channel measurements, the research program will explore the basic mechanisms that govern the dynamics of complex networks; study the development of localized high activity regions or "hot spots"; explore the dynamical correlations between the system's components and study the impact of groups and communities on network dynamics; address the dynamic vulnerabilities of complex networks, studying various topological and dynamical avenues to limit the impact of component failures. Finally, a series of models and analytical methods will be developed, aiming to turn the empirical results into predictive tools. The research program will involve the participation of postdoctoral associates, graduate students and undergraduate students. Educational activities will be further integrated with research activities by conducting an intensive weeklong summer school for undergraduate and graduate students on the fundamental aspects and applications o network theory. Also, a series of web-based lecture notes will be developed, designed to be used both in specialized network courses and as modules in existing physics, computer science or biology courses that require network analysis. ***