2015/05/27 by Juntao Chen, Quanyan Zhu, Chen, Juntao +1
Computer Science · #Distributed #Distributed Control Multi-Agent Systems #FOS: Computer and information sciences #FOS: Electrical engineering #Mobile Ad Hoc Networks #Parallel #Robotics (cs.RO) #Security in Wireless Sensor Networks #Systems and Control (eess.SY) #and Cluster Computing (cs.DC) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1505.07158
openalex publication_date 2015/05/27 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
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.