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Network connectivity plays an important role in the information exchangebetween different agents in the multi-level networks. In this paper, weestablish a game-theoretic framework to capture the uncoordinated nature of thedecision-making at different layers of the multi-level networks. Specifically,we design a decentralized algorithm that aims to maximize the algebraicconnectivity of the global network iteratively. In addition, we show that thedesigned algorithm converges to a Nash equilibrium asymptotically and yields anequilibrium network. To study the network resiliency, we introduce threeadversarial attack models and characterize their worst-case impacts on thenetwork performance. Case studies based on a two-layer mobile robotic networkare used to corroborate the effectiveness and resiliency of the proposedalgorithm and show the interdependency between different layers of the networkduring the recovery processes.

Resilient and Decentralized Control of Multi-level Cooperative Mobile Networks to Maintain Connectivity under Adversarial Environment