Construction of the Sparsest Maximally r-Robust Graphs

Fuente: arXiv
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Autores principales: Lee, Haejoon, Panagou, Dimitra
Formato: Preprint
Publicado: 2024
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author Lee, Haejoon
Panagou, Dimitra
author_facet Lee, Haejoon
Panagou, Dimitra
contents In recent years, the notion of r-robustness for the communication graph of the network has been introduced to address the challenge of achieving consensus in the presence of misbehaving agents. Higher r-robustness typically implies higher tolerance to malicious information towards achieving resilient consensus, but it also implies more edges for the communication graph. This in turn conflicts with the need to minimize communication due to limited resources in real-world applications (e.g., multi-robot networks). In this paper, our contributions are twofold. (a) We provide the necessary subgraph structures and tight lower bounds on the number of edges required for graphs with a given number of nodes to achieve maximum robustness. (b) We then use the results of (a) to introduce two classes of graphs that maintain maximum robustness with the least number of edges. Our work is validated through a series of simulations.
format Preprint
id arxiv_https___arxiv_org_abs_2409_19465
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Construction of the Sparsest Maximally r-Robust Graphs
Lee, Haejoon
Panagou, Dimitra
Systems and Control
In recent years, the notion of r-robustness for the communication graph of the network has been introduced to address the challenge of achieving consensus in the presence of misbehaving agents. Higher r-robustness typically implies higher tolerance to malicious information towards achieving resilient consensus, but it also implies more edges for the communication graph. This in turn conflicts with the need to minimize communication due to limited resources in real-world applications (e.g., multi-robot networks). In this paper, our contributions are twofold. (a) We provide the necessary subgraph structures and tight lower bounds on the number of edges required for graphs with a given number of nodes to achieve maximum robustness. (b) We then use the results of (a) to introduce two classes of graphs that maintain maximum robustness with the least number of edges. Our work is validated through a series of simulations.
title Construction of the Sparsest Maximally r-Robust Graphs
topic Systems and Control
url https://arxiv.org/abs/2409.19465