Differentially Private Consensus for Second-Order Multiagent Systems With Quantized Communication

【Author】 Zhang, Wenjun; Wang, Bing-Chang; Liang, Yong

【Source】IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS

【影响因子】14.255

【Abstract】This article considers the differentially private consensus problem of discrete-time second-order multiagent systems with partially measurable states and limited communication channel capacity, where only the integer-value information of agents can be transmitted. To reduce the potential risk of state information disclosure in digital communication, a differentially private consensus algorithm via dynamic encoding-decoding is proposed for the second-order multiagent system to make agents achieve mean-square consensus by transmitting quantized integer values with privacy protection. To deal with the uncertainty of the quantizer saturation, the statistical analysis is given for the boundedness of the input of quantizers. It is shown that the expectation of the minimum memory capacity of quantizers is 2 bits. Finally, some simulation results are given to visualize our conclusions.

【Keywords】Privacy; Differential privacy; Consensus algorithm; Protocols; Multi-agent systems; Vehicle dynamics; Symmetric matrices; Differential privacy; mean-square consensus; multiagent systems; quantized communication; stochastic system

【发表时间】

【收录时间】2022-10-30

【文献类型】实验仿真

【主题类别】

区块链技术-核心技术-共识机制