Iterative Byzantine Vector Consensus in Incomplete Graphs
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Abstract (arXiv)
This work addresses Byzantine vector consensus (BVC), wherein the input at each process is a d-dimensional vector of reals, and each process is expected to decide on a decision vector that is in the convex hull of the input vectors at the fault-free processes [3, 8]. The input vector at each process may also be viewed as a point in the d-dimensional Euclidean space R^d, where d > 0 is a finite integer. Recent work [3, 8] has addressed Byzantine vector consensus in systems that can be modeled by a complete graph. This paper considers Byzantine vector consensus in incomplete graphs. In particular, we address a particular class of iterative algorithms in incomplete graphs, and prove a necessary condition, and a sufficient condition, for the graphs to be able to solve the vector consensus problem iteratively. We present an iterative Byzantine vector consensus algorithm, and prove it correct under the sufficient condition. The necessary condition presented in this paper for vector consensus does not match with the sufficient condition for d > 1; thus, a weaker condition may potentially suffice for Byzantine vector consensus.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Jul 2013.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 3; 2025: 1.
6 papers.
- 2024Unified Breakdown Analysis for Byzantine Robust Gossipcited by 8
- 2024A survey on secure decentralized optimization and learningcited by 4
- 2021Resilient Consensus-based Multi-agent Reinforcement Learning with Function Approximationcited by 1
- 2024Byzantine-Robust Gossip: Insights from a Dual Approachcited by 1
- 2023Network Fault-tolerant and Byzantine-resilient Social Learning via Collaborative Hierarchical Non-Bayesian Learningcited by 0
- 2025ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learningcited by 0
- 2025ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning18 Jun 2025
- 2024Unified Breakdown Analysis for Byzantine Robust Gossip14 Oct 2024
- 2024A survey on secure decentralized optimization and learning16 Aug 2024
- 2024Byzantine-Robust Gossip: Insights from a Dual Approach6 May 2024
- 2023Network Fault-tolerant and Byzantine-resilient Social Learning via Collaborative Hierarchical Non-Bayesian Learning27 Jul 2023
- 2021Resilient Consensus-based Multi-agent Reinforcement Learning with Function Approximation12 Nov 2021