Chen Wei, Wang Zidong, Hu Jun, Liu Guo-Ping
IEEE Trans Cybern. 2023 Oct;53(10):6725-6736. doi: 10.1109/TCYB.2022.3233296. Epub 2023 Sep 15.
This article is concerned with the differentially private average consensus (DPAC) problem for a class of multiagent systems with quantized communication. By constructing a pair of auxiliary dynamic equations, a logarithmic dynamic encoding-decoding (LDED) scheme is developed and then utilized during the process of data transmission, thereby eliminating the effect of quantization errors on the consensus accuracy. The primary purpose of this article is to establish a unified framework that integrates the convergence analysis, the accuracy evaluation, and the privacy level for the developed DPAC algorithm under the LDED communication scheme. By means of the matrix eigenvalue analysis method, the Jury stability criterion, and the probability theory, a sufficient condition (with respect to the quantization accuracy, the coupling strength, and the communication topology) is first derived to ensure the almost sure convergence of the proposed DPAC algorithm, and the convergence accuracy and privacy level are thoroughly investigated by resorting to the Chebyshev inequality and ϵ -differential privacy index. Finally, simulation results are provided to illustrate the correctness and validity of the developed algorithm.
本文关注一类具有量化通信的多智能体系统的差分隐私平均一致性(DPAC)问题。通过构建一对辅助动态方程,开发了一种对数动态编码 - 解码(LDED)方案,并在数据传输过程中加以利用,从而消除量化误差对一致性精度的影响。本文的主要目的是建立一个统一框架,该框架整合了在LDED通信方案下所开发的DPAC算法的收敛性分析、精度评估和隐私级别。借助矩阵特征值分析方法、 Jury稳定性判据和概率论,首先推导出一个充分条件(关于量化精度、耦合强度和通信拓扑),以确保所提出的DPAC算法几乎必然收敛,并通过切比雪夫不等式和ϵ - 差分隐私指数深入研究收敛精度和隐私级别。最后,给出仿真结果以说明所开发算法的正确性和有效性。