Concentrated differentially private average consensus algorithm for a discrete-time network with heterogeneous dynamics

【Author】 Liu, Xiao-Kang; Wang, Yan-Wu; Xiao, Jiang-Wen; Chi, Ming; Liu, Zhi-Wei

【Source】JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS

【影响因子】4.246

【Abstract】This paper presents a privacy-preserving average consensus algorithm for a discrete-time network with heterogeneous dynamic nodes in the presence of Gaussian privacy noises. Renyi divergence is used to measure the privacy, and a distributed algorithm is proposed for each node in the network to protect the initial output state and ensure consensus almost surely. The convergence rate of the proposed algorithm relates to the communication topology, dynamics of systems, and decaying rates of privacy noises. Moreover, by increasing neighbors of nodes in the network, the proposed algorithm can strengthen preservation. To demonstrate the theoretical results, a numerical example is carried out on a network of one hundred nodes. (C) 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

【Keywords】

【发表时间】2022 MAR

【收录时间】2022-06-19

【文献类型】实证性文章

【主题类别】

区块链技术-核心技术-分布式存储