Distributed Algorithms
Linear Systems
Dissemination of Information in Communication Networks: Broadcasting, Gossiping, Leader Election, and Fault-Tolerance (Texts in Theoretical Computer Science. An EATCS Series)
Global Clock Synchronization in Sensor Networks
IEEE Transactions on Computers
Fault-Tolerant Gathering Algorithms for Autonomous Mobile Robots
SIAM Journal on Computing
Brief paper: Synchronization in networks of identical linear systems
Automatica (Journal of IFAC)
Broadcasting with locally bounded Byzantine faults
Information Processing Letters
A new parameter for a broadcast algorithm with locally bounded Byzantine faults
Information Processing Letters
Optimal Byzantine-resilient convergence in uni-dimensional robot networks
Theoretical Computer Science
Consensus in networked multi-agent systems with adversaries
Proceedings of the 14th international conference on Hybrid systems: computation and control
Fault-tolerant and self-stabilizing mobile robots gathering
DISC'06 Proceedings of the 20th international conference on Distributed Computing
Consensus of multi-agent networks in the presence of adversaries using only local information
Proceedings of the 1st international conference on High Confidence Networked Systems
Low complexity resilient consensus in networked multi-agent systems with adversaries
Proceedings of the 15th ACM international conference on Hybrid Systems: Computation and Control
Iterative approximate byzantine consensus in arbitrary directed graphs
PODC '12 Proceedings of the 2012 ACM symposium on Principles of distributed computing
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In this paper, we study local interaction rules that enable a network of dynamic agents to synchronize to a common zero-input state trajectory despite the malicious influence of a subset of adversary agents. The agents in the networked system influence one another by sharing state or output information according to a directed, time-varying graph. The normal agents have identical dynamics modeled by linear time-invariant (LTI) systems that are weakly stable, stabilizable, and detectable. The adversary agents are assumed to be omniscient and can take any uniformly continuous state or output trajectory. We design dynamic state and output control laws under the assumption that there is either an upper bound on the number of neighbors that may be adversaries, or an upper bound on the total number of adversary agents in the network. The control laws use only local information (i.e., information from neighbors in the network) and are resilient in the sense that they are able to mitigate the malicious influence of the adversary nodes and facilitate asymptotic synchronization of the normal agents. The conditions on the network topology required for the success of the synchronization control laws are specified in terms of network robustness. Network robustness is a novel topological property that codifies the notion of sufficient redundancy of directed edges between subsets of nodes in the network.