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The complex interconnections between heterogeneous critical infrastructuresectors make the system of systems (SoS) vulnerable to natural or human-madedisasters and lead to cascading failures both within and across sectors. Hence,the robustness and resilience of the interdependent critical infrastructures(ICIs) against extreme events are essential for delivering reliable andefficient services to our society. To this end, we first establish a holisticprobabilistic network model to model the interdependencies betweeninfrastructure components. To capture the underlying failure and recoverydynamics of ICIs, we further propose a Markov decision processes (MDP) model inwhich the repair policy determines a long-term performance of the ICIs. Toaddress the challenges that arise from the curse of dimensionality of the MDP,we reformulate the problem as an approximate linear program and then simplifyit using factored graphs. We further obtain the distributed optimal control forICIs under mild assumptions. Finally, we use a case study of the interdependentpower and subway systems to corroborate the results and show that the optimalresilience resource planning and allocation can reduce the failure probabilityand mitigate the impact of failures caused by natural or artificial disasters.

Distributed and Optimal Resilient Planning of Large-Scale Interdependent Critical Infrastructures