Harnessing Network Dynamics for "Smart" Infrastructure and Urban Resilience

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Motivation: Most large complex systems possess an inherent vulnerability to cascading failures. In these processes, an initially small disturbance is allowed to propagate and amplify, eventually causing large parts of the system to change behavior or fail. Examples include power outages, waves of species extinctions, and financial panics. As such, cascade forecasting and defense is of paramount importance in a range of applications. Research Problem: Decades of research have provided a trove of stylized insights about cascading failures, including generative mechanisms and statistical properties. Yet many practical applications demand the ability to forecast individual events, which in turn demands some knowledge the systems initial state and detailed dynamics. The latter represents a special obstacle to the study of cascades in "systems of systems" (such as the power + transportation systems), where detailed modeling understanding of the couplings between different systems remains elusive. Research Objectives: The goal of this research program is to generate deeper understanding of the dynamical foundations of cascading failures, specifically in multilayer systems. We will pursue this through three interrelated short-term research objectives, using infrastructure networks as a motivating application: 1) understanding how individual power/transportation failures in power/transportation systems induce changes in human behavior; 2) quantifying the practical limits of observability-our (or an adversary's) ability to determine ; and finally 3) designing adaptive, self-healing power systems based on time-varying networks. Anticipated Outcomes: By the end of the proposed 5-year research program, we will have identified specific dynamical features that can be exploited to predict, monitor, and counteract large-scale failures both within and between infrastructure systems. Our long-term goals are to build on these insights, moving toward accurate "systems-of-systems" modeling of urban infrastructure that accounts for the structural and dynamical heterogeneities between different infrastructure layers as well as the influence of human behavior. Impact: The insights generated here will advance the state of the art of dynamical inference, failure modeling, and control in complex systems. In the process, it will provide engineers and policymakers with new tools to fortify urban infrastructure against the threats posed by age, climate change, and deliberate attack. In addition, these tools are expected to provide insights into related network problems, including sustainable ecosystem and financial system management.