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Sensing enhancement on complex networks

Sensing enhancement on complex networks
Sensing enhancement on complex networks
Previous work has shown that communication between agents with some preference towards adopting the majority opinion can enhance the quality of error-prone individual sensing from dynamic environments. In this paper, we compare the potential of different types of complex networks for such sensing enhancement. Numerical simulations on complex networks are complemented by a mean-field approach for limited connectivity that captures essential trends in dependencies. Our results show that whilst bestowing advantages on a small group of agents degree heterogeneity tends to impede overall sensing enhancement, while clustering and spatial structure play a more nuanced role depending on overall connectivity. We find that for low connectivity sensing enhancement is maximised by random regular networks, whereas for large connectivity best sensing enhancement is found for ring graphs.
Springer
Brede, Markus
bbd03865-8e0b-4372-b9d7-cd549631f3f7
Romero Moreno, Guillermo
8c2f32d6-b0b5-4563-af22-c08b410b867f
Brede, Markus
bbd03865-8e0b-4372-b9d7-cd549631f3f7
Romero Moreno, Guillermo
8c2f32d6-b0b5-4563-af22-c08b410b867f

Brede, Markus and Romero Moreno, Guillermo (2021) Sensing enhancement on complex networks. In Proceedings of the Conference on Complex Networks and their Applications 2021. Springer.. (In Press)

Record type: Conference or Workshop Item (Paper)

Abstract

Previous work has shown that communication between agents with some preference towards adopting the majority opinion can enhance the quality of error-prone individual sensing from dynamic environments. In this paper, we compare the potential of different types of complex networks for such sensing enhancement. Numerical simulations on complex networks are complemented by a mean-field approach for limited connectivity that captures essential trends in dependencies. Our results show that whilst bestowing advantages on a small group of agents degree heterogeneity tends to impede overall sensing enhancement, while clustering and spatial structure play a more nuanced role depending on overall connectivity. We find that for low connectivity sensing enhancement is maximised by random regular networks, whereas for large connectivity best sensing enhancement is found for ring graphs.

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More information

Accepted/In Press date: 2021

Identifiers

Local EPrints ID: 452046
URI: http://eprints.soton.ac.uk/id/eprint/452046
PURE UUID: 259ef83d-0b50-4e7e-bd94-6411c19c16f9
ORCID for Guillermo Romero Moreno: ORCID iD orcid.org/0000-0002-0316-8306

Catalogue record

Date deposited: 09 Nov 2021 17:34
Last modified: 10 Nov 2021 03:56

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Contributors

Author: Markus Brede
Author: Guillermo Romero Moreno ORCID iD

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