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Resilient and decentralized control of multi-level cooperative mobile networks to maintain connectivity under adversarial environment

机译:多层次协作移动网络的弹性和分散控制,以在对抗环境下保持连接

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Network connectivity plays an important role in the information exchange between different agents in the multi-level networks. In this paper, we establish a game-theoretic framework to capture the uncoordinated nature of the decision-making at different layers of the multi-level networks. Specifically, we design a decentralized algorithm that aims to maximize the algebraic connectivity of the global network iteratively. In addition, we show that the designed algorithm converges to a Nash equilibrium asymptotically and yields an equilibrium network. To study the network resiliency, we introduce three adversarial attack models and characterize their worst-case impacts on the network performance. Case studies based on a two-layer mobile robotic network are used to corroborate the effectiveness and resiliency of the proposed algorithm and show the interdependency between different layers of the network during the recovery processes.
机译:网络连接在多层网络中不同代理之间的信息交换中起着重要作用。在本文中,我们建立了一个博弈论框架,以捕获多层网络不同层上决策的不协调性质。具体来说,我们设计了一种分散算法,旨在迭代地最大化全局网络的代数连接性。此外,我们证明了所设计的算法渐近收敛于Nash平衡并产生了一个平衡网络。为了研究网络弹性,我们介绍了三种对抗性攻击模型,并描述了它们对网络性能的最坏情况影响。基于两层移动机器人网络的案例研究用于证实所提出算法的有效性和弹性,并显示了恢复过程中网络不同层之间的相互依赖性。

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