Resilient multi-dimensional consensus in adversarial environment
This paper considers the multi-dimensional consensus in networked systems, where some of the agents might be misbehaving (or faulty). Despite the influence of these misbehaviors, the benign agents aim to reach an agreement while avoiding being seriously influenced by the faulty ones. To this end, th...
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sg-ntu-dr.10356-1635532022-12-09T01:18:03Z Resilient multi-dimensional consensus in adversarial environment Yan, Jiaqi Li, Xiuxian Mo, Yilin Wen, Changyun School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Resilient Algorithms Robust Graphs This paper considers the multi-dimensional consensus in networked systems, where some of the agents might be misbehaving (or faulty). Despite the influence of these misbehaviors, the benign agents aim to reach an agreement while avoiding being seriously influenced by the faulty ones. To this end, this paper first considers a general class of consensus algorithms, where each benign agent computes an “auxiliary point” based on the received values and moves its state towards this point. Concerning this generic form, we present conditions for achieving resilient consensus and obtain a lower bound on the exponential convergence rate. Assuming that the number of malicious agents is upper bounded, two specific resilient consensus algorithms are further developed based on the obtained conditions. Particularly, the first solution, based on Helly's Theorem, achieves the consensus within the convex hull formed by the benign agents’ initial states, where the auxiliary point can be efficiently computed through linear programming. On the other hand, the second algorithm serves as a “built-in” security guarantee for standard average consensus algorithms, in the sense that its performance coincides exactly with that of the standard ones in the absence of faulty nodes while also resisting the serious influence of the misbehaving ones in adversarial environment. Some numerical examples are provided in the end to verify the theoretical results. Ministry of Education (MOE) This work was supported by the National Key Research and Development Program of China under Grant 2018AAA0101601, the Ministry of Education (MOE), Singapore under Grant MOE2020-T1-1-067, and the National Natural Science Foundation of China under Grant 62003243. 2022-12-09T01:18:03Z 2022-12-09T01:18:03Z 2022 Journal Article Yan, J., Li, X., Mo, Y. & Wen, C. (2022). Resilient multi-dimensional consensus in adversarial environment. Automatica, 145, 110530-. https://dx.doi.org/10.1016/j.automatica.2022.110530 0005-1098 https://hdl.handle.net/10356/163553 10.1016/j.automatica.2022.110530 2-s2.0-85135945255 145 110530 en MOE2020-T1-1-067 Automatica © 2022 Elsevier Ltd. All rights reserved. |
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Engineering::Electrical and electronic engineering Resilient Algorithms Robust Graphs Yan, Jiaqi Li, Xiuxian Mo, Yilin Wen, Changyun Resilient multi-dimensional consensus in adversarial environment |
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This paper considers the multi-dimensional consensus in networked systems, where some of the agents might be misbehaving (or faulty). Despite the influence of these misbehaviors, the benign agents aim to reach an agreement while avoiding being seriously influenced by the faulty ones. To this end, this paper first considers a general class of consensus algorithms, where each benign agent computes an “auxiliary point” based on the received values and moves its state towards this point. Concerning this generic form, we present conditions for achieving resilient consensus and obtain a lower bound on the exponential convergence rate. Assuming that the number of malicious agents is upper bounded, two specific resilient consensus algorithms are further developed based on the obtained conditions. Particularly, the first solution, based on Helly's Theorem, achieves the consensus within the convex hull formed by the benign agents’ initial states, where the auxiliary point can be efficiently computed through linear programming. On the other hand, the second algorithm serves as a “built-in” security guarantee for standard average consensus algorithms, in the sense that its performance coincides exactly with that of the standard ones in the absence of faulty nodes while also resisting the serious influence of the misbehaving ones in adversarial environment. Some numerical examples are provided in the end to verify the theoretical results. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Yan, Jiaqi Li, Xiuxian Mo, Yilin Wen, Changyun |
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Article |
author |
Yan, Jiaqi Li, Xiuxian Mo, Yilin Wen, Changyun |
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Yan, Jiaqi |
title |
Resilient multi-dimensional consensus in adversarial environment |
title_short |
Resilient multi-dimensional consensus in adversarial environment |
title_full |
Resilient multi-dimensional consensus in adversarial environment |
title_fullStr |
Resilient multi-dimensional consensus in adversarial environment |
title_full_unstemmed |
Resilient multi-dimensional consensus in adversarial environment |
title_sort |
resilient multi-dimensional consensus in adversarial environment |
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2022 |
url |
https://hdl.handle.net/10356/163553 |
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1753801118085808128 |