Tolerance-based disruption-tolerant consensus in directed networks

Agathe Bouis; Christopher Lowe; Ruaridh Clark; Malcolm Macdonald

doi:10.1007/978-3-031-53503-1_37

Tolerance-based disruption-tolerant consensus in directed networks

Agathe Bouis, Christopher Lowe, Ruaridh Clark, Malcolm Macdonald

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

Abstract

This article addresses the problem of resilient consensus for multi-agent networks. Resilience is used here to distinguish disruptive agents from compliant agents which follow a given control law. We present an algorithm enabling efficient and resilient network consensus based on an inversion of the social dynamics of the Deffuant model with emotions. This is achieved through the exploitation of a dynamic tolerance linked to extremism and clustering, whereby agents filter out extreme non-standard opinions driving them away from consensus. This method is not dependent on prior knowledge of either the network topology or the number of disruptive agents, making it suitable for real-world applications where this information is typically unavailable.

Original language	English
Title of host publication	Complex Networks & Their Applications XII
Subtitle of host publication	Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023
Editors	Hocine Cherifi, Luis M. Rocha, Chantal Cherifi, Murat Donduran
Place of Publication	Cham
Publisher	Springer
Pages	449-460
Number of pages	12
Volume	4
ISBN (Electronic)	9783031535031
ISBN (Print)	9783031535024
DOIs	https://doi.org/10.1007/978-3-031-53503-1_37
Publication status	Published - 29 Feb 2024
Event	Complex Networks 2023 - Menton Riviera, France Duration: 28 Nov 2023 → 30 Nov 2023

Publication series

Name	Studies in Computational Intelligence
Volume	1144
ISSN (Print)	1860-949X
ISSN (Electronic)	1860-9503

Conference

Conference	Complex Networks 2023
Country/Territory	France
City	Menton Riviera
Period	28/11/23 → 30/11/23

Keywords

consensus algorithm
fault tolerance
social dynamics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-031-53503-1_37

Cite this

Bouis, A., Lowe, C., Clark, R., & Macdonald, M. (2024). Tolerance-based disruption-tolerant consensus in directed networks. In H. Cherifi, L. M. Rocha, C. Cherifi, & M. Donduran (Eds.), Complex Networks & Their Applications XII: Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023 (Vol. 4, pp. 449-460). (Studies in Computational Intelligence; Vol. 1144). Springer. https://doi.org/10.1007/978-3-031-53503-1_37

Bouis, Agathe ; Lowe, Christopher ; Clark, Ruaridh et al. / Tolerance-based disruption-tolerant consensus in directed networks. Complex Networks & Their Applications XII: Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023. editor / Hocine Cherifi ; Luis M. Rocha ; Chantal Cherifi ; Murat Donduran. Vol. 4 Cham : Springer, 2024. pp. 449-460 (Studies in Computational Intelligence).

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abstract = "This article addresses the problem of resilient consensus for multi-agent networks. Resilience is used here to distinguish disruptive agents from compliant agents which follow a given control law. We present an algorithm enabling efficient and resilient network consensus based on an inversion of the social dynamics of the Deffuant model with emotions. This is achieved through the exploitation of a dynamic tolerance linked to extremism and clustering, whereby agents filter out extreme non-standard opinions driving them away from consensus. This method is not dependent on prior knowledge of either the network topology or the number of disruptive agents, making it suitable for real-world applications where this information is typically unavailable.",

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Bouis, A, Lowe, C, Clark, R & Macdonald, M 2024, Tolerance-based disruption-tolerant consensus in directed networks. in H Cherifi, LM Rocha, C Cherifi & M Donduran (eds), Complex Networks & Their Applications XII: Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023. vol. 4, Studies in Computational Intelligence, vol. 1144, Springer, Cham, pp. 449-460, Complex Networks 2023, Menton Riviera, France, 28/11/23. https://doi.org/10.1007/978-3-031-53503-1_37

Tolerance-based disruption-tolerant consensus in directed networks. / Bouis, Agathe; Lowe, Christopher; Clark, Ruaridh et al.
Complex Networks & Their Applications XII: Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023. ed. / Hocine Cherifi; Luis M. Rocha; Chantal Cherifi; Murat Donduran. Vol. 4 Cham: Springer, 2024. p. 449-460 (Studies in Computational Intelligence; Vol. 1144).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

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N1 - Copyright © 2024 Springer-Verlag. This version of the paper has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at https://doi.org/10.1007/978-3-031-53503-1_37

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AB - This article addresses the problem of resilient consensus for multi-agent networks. Resilience is used here to distinguish disruptive agents from compliant agents which follow a given control law. We present an algorithm enabling efficient and resilient network consensus based on an inversion of the social dynamics of the Deffuant model with emotions. This is achieved through the exploitation of a dynamic tolerance linked to extremism and clustering, whereby agents filter out extreme non-standard opinions driving them away from consensus. This method is not dependent on prior knowledge of either the network topology or the number of disruptive agents, making it suitable for real-world applications where this information is typically unavailable.

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Bouis A, Lowe C, Clark R , Macdonald M. Tolerance-based disruption-tolerant consensus in directed networks. In Cherifi H, Rocha LM, Cherifi C, Donduran M, editors, Complex Networks & Their Applications XII: Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023. Vol. 4. Cham: Springer. 2024. p. 449-460. (Studies in Computational Intelligence). doi: 10.1007/978-3-031-53503-1_37

Tolerance-based disruption-tolerant consensus in directed networks

Abstract

Publication series

Conference

Keywords

UN SDGs

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An aUtonomous DistrIbuted Time signal in-Space (AUDITS)

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Tolerance-based disruption-tolerant consensus in directed networks

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

Other files and links

Embargoed Document

Fingerprint

Projects

An aUtonomous DistrIbuted Time signal in-Space (AUDITS)

Cite this