Cyberphysical (CPS) systems are set to become ever faster, driven by technological advances that push them toward speed limits set by fundamental physics. This proposal addresses the need for a theory of the dynamical behavior of CPS systems in the sub-second regime beyond human intervention times. Ultrafast instabilities have already been observed in such systems. The theory will allow for networking at multiple scales, coupling across multiple temporal and spatial scales, imperfect network communications and sensors, as well as adaptive reorganization and reconfiguration of the system. Theoretical findings will be checked against available empirical data, e.g., from the decentralized network of autonomous market exchanges with its mandated sensor systems. The project will inform the extent to which instabilities can build up across timescales, potentially threatening CPS system stability on a global level.

The project goal is a theoretical description of the dynamics in decentralized networks of semi-autonomous machines in which an ecology of algorithms, sensors and network links may be operating, adapting and even competing in response to external inputs. Attention will be paid to the regime of sub-second behavior where human intervention becomes impossible in real-time. The availability of data from such a system provides a test-bed for the multi-agent, complex network analyses to be developed. The project will address how instabilities can be mitigated and eventually controlled. The results are set to advance understanding of CPS system dynamics, not only among academics but also practitioners and regulatory bodies. Application areas that pervade modern life include market exchange systems, resource-allocation systems and remote sensing systems. Opportunities exist to integrate research and education concerning CPS applications across graduate and undergraduate classrooms, outreach through publications, and participation in K-12 activities.

National Science Foundation (NSF)
Division of Computer and Network Systems (CNS)
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David Corman
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University of Miami
Coral Gables
United States
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