ABSTRACT
In the past decade, numerous consensus protocols for networked multi-agent systems have been proposed. Although some forms of robustness of these algorithms have been studied, reaching consensus securely in networked multi-agent systems, in spite of intrusions caused by malicious agents, or adversaries, has been largely underexplored. In this work, we consider a general model for adversaries in Euclidean space and introduce a consensus problem for networked multi-agent systems similar to the Byzantine consensus problem in distributed computing. We present the Adversarially Robust Consensus Protocol (ARC-P), which combines ideas from consensus algorithms that are resilient to Byzantine faults and from linear consensus protocols used for control and coordination of dynamic agents. We show that ARC-P solves the consensus problem in complete networks whenever there are more cooperative agents than adversaries. Finally, we illustrate the resilience of ARC-P to adversaries through simulations and compare ARC-P with a linear consensus protocol for networked multi-agent systems.
- N. Agmon and D. Peleg. Fault-tolerant gathering algorithms for autonomous mobile robots. SIAM J. Comput., 36(1):56--82, 2006. Google ScholarDigital Library
- F. Blanchini. Set invariance in control. Automatica, 35(11):1747--1767, 1999. Google ScholarDigital Library
- F. Blanchini and S. Miani. Set-Theoretic Methods in Control. Birkhauser, Boston, Massachusetts, 2008. Google ScholarDigital Library
- Z. Bouzid, M. Gradinariu Potop-Butucaru, and S. Tixeuil. Byzantine convergence in robot networks: The price of asynchrony. In Int. Conf. on Principles of Distributed Systems, pages 54--70, December 2009. Google ScholarDigital Library
- M. H. DeGroot. Reaching a consensus. Journal of the American Statistical Association, 69(345):118--121, 1974.Google ScholarCross Ref
- D. Dolev, N. A. Lynch, S. S. Pinter, E. W. Stark, and W. E. Weihl. Reaching approximate agreement in the presence of faults. Journal of the ACM, 33(3):499--516, 1986. Google ScholarDigital Library
- A. Fagiolini, F. Babboni, and A. Bicchi. Dynamic distributed intrusion detection for secure multi-robot systems. In Int. Conf. of Robotics and Aut., pages 2723--2728, May 2009. Google ScholarDigital Library
- A. Fagiolini, A. Bicchi, G. Dini, and I. Savino. Tolerating malicious monitors in detecting misbehaving robots. In IEEE Int. Workshop on Safety, Security, and Rescue Robotics, pages 108--114, October 2008.Google Scholar
- A. Fagiolini, M. Pellinacci, M. Valenti, G., G. Dini, and A. Bicchi. Consensus-based distributed intrusion detection for multi-robot systems. In Int. Conf. on Robotics and Aut., pages 120--127, May 2008.Google ScholarCross Ref
- J. A. Fax and R. M. Murray. Information flow and cooperative control of vehicle formations. IEEE Trans. on Aut. Control, 49(9):1465--1476, 2004.Google ScholarCross Ref
- S. Gilbert, N. Lynch, S. Mitra, and T. Nolte. Self-stabilizing robot formations over unreliable networks. ACM Trans. Auton. Adapt. Syst., 4(3):1--29, 2009. Google ScholarDigital Library
- V. Gupta, C. Langbort, and R. Murray. On the robustness of distributed algorithms. In IEEE Conf. on Decision and Control, December 2006.Google ScholarCross Ref
- P. Hovareshti, J. Baras, and V. Gupta. Average consensus over small world networks: A probabilistic framework. In IEEE Conf. on Decision and Control, December 2008.Google ScholarCross Ref
- M. Huang and J. Manton. Stochastic Lyapunov analysis for consensus algorithms with noisy measurements. In American Control Conf., July 2007.Google ScholarCross Ref
- Q. Hui, W. Haddad, and S. Bhat. On robust control algorithms for nonlinear network consensus protocols. Int. J. Robust Nonlinear Control, 20(3):269--284, 2010.Google ScholarCross Ref
- L. Lamport, R. Shostak, and M. Pease. The Byzantine generals problem. ACM Trans. Program. Lang. Syst., 4(2):382--401, 1982. Google ScholarDigital Library
- D. Lee and M. Spong. Agreement with non-uniform information delays. In American Control Conf., pages 756--761, June 2006.Google Scholar
- N. A. Lynch. Distributed Algorithms. Morgan Kaufmann Publishers Inc., San Francisco, California, 1997. Google ScholarDigital Library
- M. Mesbahi and M. Egerstedt. Graph Theoretic Methods in Multiagent Networks. Princeton University Press, Princeton, New Jersey, 2010.Google Scholar
- R. Olfati-Saber. Ultrafast consensus in small-world networks. In American Control Conf., pages 2371--2378, June 2005.Google ScholarCross Ref
- R. Olfati-Saber, J. A. Fax, and R. M. Murray. Consensus and cooperation in networked multi-agent systems. Proceedings of the IEEE, 95(1):215--233, 2007.Google ScholarCross Ref
- R. Olfati-Saber, E. Franco, E. Frazzoli, and J. Shamma. Belief consensus and distributed hypothesis testing in sensor networks. In Networked Embedded Sensing and Control, volume 331 of Lecture Notes in Control and Information Sciences, pages 169--182. Springer Berlin / Heidelberg, 2006.Google Scholar
- R. Olfati-Saber and R. M. Murray. Consensus problems in networks of agents with switching topology and time-delays. IEEE Trans. on Aut. Control, 49(9):1520--1533, September 2004.Google ScholarCross Ref
- L. Pallottino, V. G. Scordio, E. Frazzoli, and A. Bicchi. Decentralized cooperative policy for conflict resolution in multi-vehicle systems. IEEE Trans. on Robotics, 23(6):1170--1183, 2007. Google ScholarDigital Library
- F. Pasqualetti, A. Bicchi, and F. Bullo. Distributed intrusion detection for secure consensus computations. In IEEE Conf. on Decision and Control, pages 5594--5599, December 2007.Google ScholarCross Ref
- F. Pasqualetti, A. Bicchi, and F. Bullo. On the security of linear consensus networks. In IEEE Conf. on Decision and Control, December 2009.Google ScholarCross Ref
- F. Pasqualetti, R. Carli, A. Bicchi, and F. Bullo. Identifying cyber attacks via local model information. In IEEE Conf. on Decision and Control, December 2010.Google ScholarCross Ref
- M. Pease, R. Shostak, and L. Lamport. Reaching agreement in the presence of faults. J. ACM, 27(2):228--234, 1980. Google ScholarDigital Library
- G. Prencipe. CORDA: Distributed coordination of a set of autonomous mobile robots. In Proc. 4th European Research Seminar on Advances in Distributed Systems, pages 185--190, May 2001.Google Scholar
- D. Spanos, R. Olfati-Saber, and R. Murray. Approximate distributed Kalman filtering in sensor networks with quantifiable performance. In 4th Int. Symp. on Information Processing in Sensor Networks, pages 133--139, April 2005. Google ScholarDigital Library
- S. Sundaram and C. Hadjicostis. Distributed function calculation via linear iterations in the presence of malicious agents; part II: Overcoming malicious behavior. In American Control Conf., pages 1356--1361, June 2008.Google ScholarCross Ref
- I. Suzuki and M. Yamashita. Distributed anonymous mobile robots: Formation of geometric patterns. SIAM Journal on Computing, 28:1347--1363, 1999. Google ScholarDigital Library
- H. Tanner, G. Pappas, and V. Kumar. Leader-to-formation stability. IEEE Trans. on Robotics and Automation, 20(3):443--455, 2004.Google ScholarCross Ref
- S. Vanka, V. Gupta, and M. Haenggi. Power-delay analysis of consensus algorithms on wireless networks with interference. Int. J. Syst., Control Commun., 2(1/2/3):256--274, 2010. Google ScholarDigital Library
- W. Wang and J.-J. Slotine. Contraction analysis of time-delayed communications and group cooperation. IEEE Trans. on Aut. Control, 51(4):712--717, April 2006.Google ScholarCross Ref
- L. Xiao, S. Boyd, and S. Lall. A scheme for robust distributed sensor fusion based on average consensus. In 4th Int. Symp. on Information Processing in Sensor Networks, pages 63--70, April 2005. Google ScholarDigital Library
Index Terms
- Consensus in networked multi-agent systems with adversaries
Recommendations
Low complexity resilient consensus in networked multi-agent systems with adversaries
HSCC '12: Proceedings of the 15th ACM international conference on Hybrid Systems: Computation and ControlRecently, many applications have arisen in distributed control that require consensus protocols. Concurrently, we have seen a proliferation of malicious attacks on large-scale distributed systems. Hence, there is a need for (i) consensus problems that ...
Consensus of multi-agent networks in the presence of adversaries using only local information
HiCoNS '12: Proceedings of the 1st international conference on High Confidence Networked SystemsThis paper addresses the problem of resilient consensus in the presence of misbehaving nodes. Although it is typical to assume knowledge of at least some nonlocal information when studying secure and fault-tolerant consensus algorithms, this assumption ...
Consensus in multi-agent systems: a review
AbstractThis paper provides a review of the consensus problem as one of the most challenging issues in the distributed control of the multi-agent systems (MASs). In this survey, firstly, the consensus algorithms for the agents with the single-integrator, ...
Comments