Robust Average Consensus under Byzantine Attacks
We study the problem of average consensus in multi-agent systems where some of the agents may malfunction. The object of robust average consensus is for non-faulty agents to converge to the average value of their initial values despite the erroneous effects from adversarial agents. To this end, we p...
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| Vydáno v: | Proceedings of the IEEE Conference on Decision & Control s. 3839 - 3844 |
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IEEE
16.12.2024
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| ISSN: | 2576-2370 |
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| Abstract | We study the problem of average consensus in multi-agent systems where some of the agents may malfunction. The object of robust average consensus is for non-faulty agents to converge to the average value of their initial values despite the erroneous effects from adversarial agents. To this end, we propose a surplus-based consensus algorithm that can achieve robust average consensus under Byzantine attacks in the multi-agent networks with directed topologies. The key idea is to equip each normal agent with a running-sum variable so that it can record the effects from/to neighbors across iterations. Moreover, compared to the existing secure broadcast and retrieval approach where each agent keeps track of the initial values of all agents in the network, our algorithm saves massive storage especially for large-scale networks as each agent only requires the values and the correct detection of neighbors. Finally, numerical examples are given for verifying the effectiveness of our algorithm. |
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| AbstractList | We study the problem of average consensus in multi-agent systems where some of the agents may malfunction. The object of robust average consensus is for non-faulty agents to converge to the average value of their initial values despite the erroneous effects from adversarial agents. To this end, we propose a surplus-based consensus algorithm that can achieve robust average consensus under Byzantine attacks in the multi-agent networks with directed topologies. The key idea is to equip each normal agent with a running-sum variable so that it can record the effects from/to neighbors across iterations. Moreover, compared to the existing secure broadcast and retrieval approach where each agent keeps track of the initial values of all agents in the network, our algorithm saves massive storage especially for large-scale networks as each agent only requires the values and the correct detection of neighbors. Finally, numerical examples are given for verifying the effectiveness of our algorithm. |
| Author | Wang, Yaonan Ishii, Hideaki Yuan, Liwei |
| Author_xml | – sequence: 1 givenname: Liwei surname: Yuan fullname: Yuan, Liwei email: yuanliwei@hnu.edu.cn organization: Hunan University,College of Electrical and Information Engineering,Changsha,China,410082 – sequence: 2 givenname: Hideaki surname: Ishii fullname: Ishii, Hideaki email: hideaki_ishii@ipc.i.u-tokyo.ac.jp organization: The University of Tokyo,Department of Information Physics and Computing,Tokyo,Japan,113-8656 – sequence: 3 givenname: Yaonan surname: Wang fullname: Wang, Yaonan email: yaonan@hnu.edu.cn organization: Hunan University,College of Electrical and Information Engineering,Changsha,China,410082 |
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| Snippet | We study the problem of average consensus in multi-agent systems where some of the agents may malfunction. The object of robust average consensus is for... |
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| SubjectTerms | Consensus algorithm Economics Multi-agent systems Network topology Topology |
| Title | Robust Average Consensus under Byzantine Attacks |
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