research-article

Algorithms for determining network robustness

Authors:

Heath J. LeBlanc,

Xenofon D. KoutsoukosAuthors Info & Claims

HiCoNS '13: Proceedings of the 2nd ACM international conference on High confidence networked systems

Pages 57 - 64

https://doi.org/10.1145/2461446.2461455

Published: 09 April 2013 Publication History

Abstract

In this paper, we study algorithms for determining the robustness of a network. Network robustness is a novel graph theoretic property that provides a measure of redundancy of directed edges between all pairs of nonempty, disjoint subsets of nodes in a graph. The robustness of a graph has been shown recently to be useful for characterizing the class of network topologies in which resilient distributed algorithms that use purely local strategies are able to succeed in the presence of adversary nodes. Therefore, network robustness is a critical property of resilient networked systems. While methods have been given to construct robust networks, algorithms for determining the robustness of a given network have not been explored. This paper introduces several algorithms for determining the robustness of a network, and includes centralized, decentralized, and distributed algorithms.

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Cited By

Jiang JWu YZhang ZZheng NMeng W(2024) Determining - and ( , )-robustness of multiagent networks based on heuristic algorithm Neurocomputing10.1016/j.neucom.2024.128025598(128025)Online publication date: Sep-2024
https://doi.org/10.1016/j.neucom.2024.128025
Gao RYang G(2024)Resilient cluster consensus for discrete-time high-order multi-agent systems against malicious adversariesAutomatica10.1016/j.automatica.2023.111382159(111382)Online publication date: Jan-2024
https://doi.org/10.1016/j.automatica.2023.111382
Yu XSaldana DShishika DHsieh M(2022)Resilient Consensus in Robot Swarms With Periodic Motion and Intermittent CommunicationIEEE Transactions on Robotics10.1109/TRO.2021.308876538:1(110-125)Online publication date: Feb-2022
https://doi.org/10.1109/TRO.2021.3088765
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Index Terms

Algorithms for determining network robustness
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
  2. Dependable and fault-tolerant systems and networks
2. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Distributed systems organizing principles

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cover image ACM Conferences

HiCoNS '13: Proceedings of the 2nd ACM international conference on High confidence networked systems

April 2013

152 pages

ISBN:9781450319614

DOI:10.1145/2461446

General Chairs:
S. Shankar Sastry
University of California, Berkeley, USA
,
Tamer Başar
University of Illinois at Urbana-Champaign, USA
,
Program Chairs:
Linda Bushnell
University of Washington, USA
,
Larry Rohrbough
University of California, Berkeley, USA

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGBED: ACM Special Interest Group on Embedded Systems

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 April 2013

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HiCoNS '13

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SIGBED

HiCoNS '13: 2nd ACM International Conference on High Confidence Networked Systems

April 9 - 11, 2013

Pennsylvania, Philadelphia, USA

Acceptance Rates

HiCoNS '13 Paper Acceptance Rate 18 of 37 submissions, 49%;

Overall Acceptance Rate 30 of 55 submissions, 55%

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Cited By

Jiang JWu YZhang ZZheng NMeng W(2024) Determining - and ( , )-robustness of multiagent networks based on heuristic algorithm Neurocomputing10.1016/j.neucom.2024.128025598(128025)Online publication date: Sep-2024
https://doi.org/10.1016/j.neucom.2024.128025
Gao RYang G(2024)Resilient cluster consensus for discrete-time high-order multi-agent systems against malicious adversariesAutomatica10.1016/j.automatica.2023.111382159(111382)Online publication date: Jan-2024
https://doi.org/10.1016/j.automatica.2023.111382
Yu XSaldana DShishika DHsieh M(2022)Resilient Consensus in Robot Swarms With Periodic Motion and Intermittent CommunicationIEEE Transactions on Robotics10.1109/TRO.2021.308876538:1(110-125)Online publication date: Feb-2022
https://doi.org/10.1109/TRO.2021.3088765
Yi YWang YHe XPatterson SJohansson K(2022)A Sample-Based Algorithm for Approximately Testing r-Robustness of a Digraph2022 IEEE 61st Conference on Decision and Control (CDC)10.1109/CDC51059.2022.9993257(6478-6483)Online publication date: 6-Dec-2022
https://doi.org/10.1109/CDC51059.2022.9993257
Yan JLi XMo YWen C(2022)Resilient multi-dimensional consensus in adversarial environmentAutomatica10.1016/j.automatica.2022.110530145(110530)Online publication date: Nov-2022
https://doi.org/10.1016/j.automatica.2022.110530
Ishii HWang YFeng S(2022)An overview on multi-agent consensus under adversarial attacksAnnual Reviews in Control10.1016/j.arcontrol.2022.01.00453(252-272)Online publication date: 2022
https://doi.org/10.1016/j.arcontrol.2022.01.004
Wehbe RWilliams R(2021)Probabilistic Resilience of Dynamic Multi-Robot SystemsIEEE Robotics and Automation Letters10.1109/LRA.2021.30603786:2(1777-1784)Online publication date: Apr-2021
https://doi.org/10.1109/LRA.2021.3060378
Yu XShishika DSaldana DHsieh M(2020)Modular Robot Formation and Routing for Resilient Consensus2020 American Control Conference (ACC)10.23919/ACC45564.2020.9147563(2464-2471)Online publication date: Jul-2020
https://doi.org/10.23919/ACC45564.2020.9147563
Guerrero-Bonilla LSaldana DKumar V(2020)Dense r-robust formations on lattices2020 IEEE International Conference on Robotics and Automation (ICRA)10.1109/ICRA40945.2020.9196683(6633-6639)Online publication date: May-2020
https://doi.org/10.1109/ICRA40945.2020.9196683
Wu YHe X(2020)Finite-Time Consensus-Based Clock Synchronization Under Deception AttacksIEEE Access10.1109/ACCESS.2020.30025778(110748-110758)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3002577
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