Delay and DoS Resilient Consensus of Multi-Agent Systems: A Bit Rate Minimization Strategy

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-01-07 DOI:10.1109/TNSE.2024.3524616

Lulu Li;Huihui Zhang;Daniel W. C. Ho

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引用次数: 0

Abstract

This paper investigates the consensus issue of multi-agent systems under constrained data rates, time delays, and denial-of-service (DoS) attacks. We first introduce a periodically adjusted dynamic quantizer based on the equally distributed bit rate model, which can effectively avoid saturation and eliminate the quantization error over time, unlike the static quantizer. Then, we show that the quantizer in this paper is suitable for multi-agent systems with time delays, and we design a quantized controller that can realize the consensus in such systems. We also derive the sufficient bit rate condition for achieving consensus under time delays. Next, we extend our approach to handle multi-agent systems with both time delays and DoS attacks under the general energy-constrained DoS model. We provide the conditions on bit rate and average duration and frequency of DoS attacks that ensure system performance. Finally, we analyze the relationship between system performance, bit rate, time delays, and DoS attacks, and verify our results by numerical examples.

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多智能体系统的延迟和DoS弹性一致性：比特率最小化策略

研究了数据速率受限、时延受限和DoS攻击条件下多智能体系统的一致性问题。我们首先引入了一种基于等分布比特率模型的周期性调整动态量化器，与静态量化器不同，它可以有效地避免饱和并消除随时间推移的量化误差。然后，我们证明了本文的量化器适用于具有时滞的多智能体系统，并设计了一个量化控制器来实现这种系统的一致性。我们还推导了在时滞下达到一致的充分比特率条件。接下来，我们扩展了我们的方法来处理在一般能量约束的DoS模型下具有时间延迟和DoS攻击的多智能体系统。给出了保证系统性能的比特率、DoS攻击的平均持续时间和频率条件。最后，我们分析了系统性能、比特率、时延和DoS攻击之间的关系，并通过数值算例验证了我们的结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.