Dynamic Quantized Consensus of General Linear Multi-agent Systems under Denial-of-Service Attacks

TL;DR

This paper investigates how multi-agent systems can achieve consensus under DoS attacks and data rate constraints by deriving bounds and employing dynamic quantization techniques to prevent overflow and maintain communication.

Contribution

It characterizes the trade-off between DoS attack levels and data rate requirements, introducing dynamic quantization with zooming to enhance robustness.

Findings

Derived lower bounds on data rates for consensus under DoS attacks.

Established the trade-off between attack tolerance and data rate requirements.

Implemented dynamic quantization with zooming to prevent quantizer saturation.

Abstract

In this paper, we study multi-agent consensus problems under Denial-of-Service (DoS) attacks with data rate constraints. We first consider the leaderless consensus problem and after that we briefly present the analysis of leader-follower consensus. The dynamics of the agents take general forms modeled as homogeneous linear time-invariant systems. In our analysis, we derive lower bounds on the data rate for the multi-agent systems to achieve leaderless and leader-follower consensus in the presence of DoS attacks, under which the issue of overflow of quantizer is prevented. The main contribution of the paper is the characterization of the trade-off between the tolerable DoS attack levels for leaderless and leader-follower consensus and the required data rates for the quantizers during the communication attempts among the agents. To mitigate the influence of DoS attacks, we employ dynamic quantization with zooming-in and zooming-out capabilities for avoiding quantizer saturation.