Visible to the public A Factored MDP Approach to Optimal Mechanism Design for Resilient Large-Scale Interdependent Critical Infrastructures

TitleA Factored MDP Approach to Optimal Mechanism Design for Resilient Large-Scale Interdependent Critical Infrastructures
Publication TypeConference Paper
Year of Publication2017
AuthorsHuang, L., Chen, J., Zhu, Q.
Conference Name2017 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)
Keywordsaction spaces, approximate linear programming, approximation theory, Cascading Failures, compositionality, control theory, critical infrastructures, Cyber Dependencies, cyber-physical dependencies, decision theory, factored MDP approach, Human Behavior, human factors, large-scale interdependent critical infrastructures, large-scale interdependent system, Linear programming, Markov decision processes, Markov processes, Metrics, network resilience, network theory (graphs), optimal resiliency mechanism design, power grids, power system reliability, power system security, pubcrawl, resilience, Resiliency, Scalability, security enhancement, state spaces
Abstract

Enhancing the security and resilience of interdependent infrastructures is crucial. In this paper, we establish a theoretical framework based on Markov decision processes (MDPs) to design optimal resiliency mechanisms for interdependent infrastructures. We use MDPs to capture the dynamics of the failure of constituent components of an infrastructure and their cyber-physical dependencies. Factored MDPs and approximate linear programming are adopted for an exponentially growing dimension of both state and action spaces. Under our approximation scheme, the optimally distributed policy is equivalent to the centralized one. Finally, case studies in a large-scale interdependent system demonstrate the effectiveness of the control strategy to enhance the network resilience to cascading failures.

URLhttp://ieeexplore.ieee.org/document/8064531/
DOI10.1109/MSCPES.2017.8064531
Citation Keyhuang_factored_2017