异构多智能体系统的差分私有均方输出一致性:一种异步采样数据交互方案

IF 8 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Guoliang Chen;Lingyu Wang;Te Yang;Jianwei Xia;Ju H. Park
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引用次数: 0

摘要

研究了异步采样数据交互下具有间歇信息传递的连续时间异构多智能体系统的隐私保护平均一致性问题。为了解决特定于代理的异步采样数据和时变通信延迟带来的挑战,引入了一种包含共享采样周期策略的时间转换方法,有效地将异步问题转换为同步框架。其次,设计了具有时变噪声注入的集成分布式混合控制器,使智能体仅在采样时刻与敏感信息交互,从而在保持轨迹可用性的同时保护隐私。然后,提出了时变步长和噪声参数作为双控制机制的可调参数,对应于期望的差分隐私预算和系统收敛精度,并深入分析了控制性能与隐私保护之间的权衡。结果表明,所提出的协议在预定义的精度和隐私预算下实现了渐近无偏均方输出一致性。数值算例验证了理论结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Differentially Private Mean-Square Output Consensus for Heterogeneous Multiagent Systems: An Asynchronous Sampled-Data Interactions Scheme
This article investigates the problem of privacy-preserving average consensus for continuous-time heterogeneous multiagent systems with intermittent information transfer under asynchronous sampled-data interactions. To address the challenges posed by agent-specific asynchronous sampled-data and time-varying communication delays, a time-translation approach incorporating a shared sampling period strategy is introduced, effectively transforming the asynchronous problem into a synchronous framework. Next, integrated distributed hybrid controller with time-varying noise injection is designed, enabling agents to interact with sensitive information only at sampling instants, thereby preserving privacy while maintaining trajectory availability. Then, the time-varying step-size and noise parameters, which are tunable parameters of the dual control mechanism corresponding to the desired $\varepsilon $ -differential privacy budget and system convergence accuracy are proposed, and the trade-off between control performance and privacy preservation is thoroughly analyzed. It is shown that the proposed protocol achieves asymptotically unbiased mean-square output consensus with predefined accuracy and privacy budget. Numerical examples validate the theoretical results.
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来源期刊
IEEE Transactions on Information Forensics and Security
IEEE Transactions on Information Forensics and Security 工程技术-工程:电子与电气
CiteScore
14.40
自引率
7.40%
发文量
234
审稿时长
6.5 months
期刊介绍: The IEEE Transactions on Information Forensics and Security covers the sciences, technologies, and applications relating to information forensics, information security, biometrics, surveillance and systems applications that incorporate these features
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