Complex networks in Air Force-relevant applications, including multi-vehicle control, energy systems, and neuronal networks, are expected to guarantee performance, stability, and availability. These networks are expected to be robust against natural failures and resilient against deliberate attacks. Two critical failure modes are (i) antagonistic interactions, in which an interaction between nodes causes their state values to separate, and (ii) interdependent failures, in which the failure of a single node or edge can trigger cascading failures of other nodes and edges. Agile response to such failures requires design of an efficient monitoring system that is integrated into the network. At present, there is no computationally tractable analytical framework for modeling and designing resilient networks with provable performance guarantees.
We propose to research and develop a submodular optimization framework for resilient complex networks. Submodularity is a diminishing returns property that enables the development of computationally efficient algorithms with provable optimality bounds. Based on our extensive prior work on submodularity in network dynamics and control, we believe that many of the key metrics quantifying network stability, performance, and resilience have a submodular structure.
Meet the Team
UW & WPI Team
Prof. Linda Bushnell
Principal InvestigatorElectrical & Computer Engineering, UW
Prof. Radha Poovendran
Co-Principal InvestigatorElectrical & Computer Engineering, UW
Prof. Andrew Clark
Co-Principal InvestigatorElectrical & Computer Engineering, WPI
Dinuka SahabanduPh.D student, UW
Luyao NiuPost-doctoral scholar, UW
Abdullah Al MarufPost-doctoral scholar, UW
Our recent Publications
D. Sahabandu, A. Clark, L. Bushnell, R. Poovendran, "Submodular Input Selection for Synchronization in Kuramoto Networks", in IEEE Conference on Decision and Control (CDC), 2020.
Air Force Office of Scientific Research
University of Washington | Network Security Lab