Resilient Consensus for Multi-agent Networks with Mobile Detectors

This paper investigates the problem of resilient consensus for multi-agent systems under malicious attacks. Compared with most of existing works, a more flexible network topology scheme is considered, where a kind of specific agents as the mobile detectors and builders of network robustness are adopted. Specifically, the mobile agents can perceive the message of their nearby agents in the dynamic network, and acquire both in-degree and state information of each node as characteristics to judge the network state as well as communication links between nodes. It is shown that even in poor network robustness, the non-faulty agents can still achieve a consensus in finite time with the help of mobile agents. Finally, the simulation results show the effectiveness of the proposed method.

[1]  Roger M. Kieckhafer,et al.  Reaching Approximate Agreement with Mixed-Mode Faults , 1994, IEEE Trans. Parallel Distributed Syst..

[2]  Shuai Liu,et al.  Consensus of discrete-time multi-agent systems with adversaries and time delays , 2014, Int. J. Gen. Syst..

[3]  Hideaki Ishii,et al.  Resilient Multi-Agent Consensus with Asynchrony and Delayed Information , 2015 .

[4]  Jiming Chen,et al.  Exploiting a Mobile Node for Fast Discrete Time Average Consensus , 2016, IEEE Transactions on Control Systems Technology.

[5]  Jiming Chen,et al.  Resilient Consensus with Mobile Detectors Against Malicious Attacks , 2018, IEEE Transactions on Signal and Information Processing over Networks.

[6]  Xin-Ping Guan,et al.  A Secure Scheme for Distributed Consensus Estimation against Data Falsification in Heterogeneous Wireless Sensor Networks , 2016, Sensors.

[7]  David K. Y. Yau,et al.  Matching and Fairness in Threat-Based Mobile Sensor Coverage , 2009, IEEE Transactions on Mobile Computing.

[8]  Sergio Gómez,et al.  Size reduction of complex networks preserving modularity , 2007, ArXiv.

[9]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[10]  Long Wang,et al.  Consensus of Hybrid Multi-Agent Systems , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[11]  Shreyas Sundaram,et al.  Resilient Asymptotic Consensus in Robust Networks , 2013, IEEE Journal on Selected Areas in Communications.

[12]  Claudio Castellano,et al.  Defining and identifying communities in networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Nancy A. Lynch,et al.  Reaching approximate agreement in the presence of faults , 1986, JACM.

[14]  Lewis Tseng,et al.  Iterative approximate byzantine consensus in arbitrary directed graphs , 2012, PODC '12.

[15]  Xenofon Koutsoukos,et al.  Consensus in networked multi-agent systems with adversaries , 2011 .

[16]  Long Cheng,et al.  Containment Control of Multiagent Systems With Dynamic Leaders Based on a $PI^{n}$ -Type Approach , 2014, IEEE Transactions on Cybernetics.

[17]  R. Kieckhafer,et al.  Low Cost Approximate Agreement In Partially Connected Networks , 1993 .

[18]  Shreyas Sundaram,et al.  Robustness of information diffusion algorithms to locally bounded adversaries , 2011, 2012 American Control Conference (ACC).

[19]  Shreyas Sundaram,et al.  A Notion of Robustness in Complex Networks , 2015, IEEE Transactions on Control of Network Systems.

[20]  Xiongxiong He,et al.  Secure consensus control for multiagent systems with attacks and communication delays , 2016, IEEE/CAA Journal of Automatica Sinica.

[21]  M. Newman,et al.  Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  Sulan Li,et al.  Bipartite Consensus in Networks of Agents With Antagonistic Interactions and Quantization , 2018, IEEE Transactions on Circuits and Systems II: Express Briefs.

[23]  Yunpeng Wang,et al.  On Convergence Rate of Leader-Following Consensus of Linear Multi-Agent Systems With Communication Noises , 2015, IEEE Transactions on Automatic Control.