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Diagnostic décentralisé à l'aide d'automates cellulaires

Nicolas Gauville 1, 2, 3 Nazim Fatès 3 Irène Marcovici 4, 3
2 LARSEN - Lifelong Autonomy and interaction skills for Robots in a Sensing ENvironment
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
3 MOCQUA - Designing the Future of Computational Models
Inria Nancy - Grand Est, LORIA - FM - Department of Formal Methods
Abstract : We address the problem of detecting failures in a distributed network. If some components can break down over time, how can we detect that the failure rate has exceeded a given threshold wi- thout any central authority ? Our aim is to have an estimate of the global state of the network, only through local interactions of components with their neighbours. In particular, we wish to reach a consensus on an alert state when the failure rate exceeds a given threshold. We use the model of cellular automata in order to pro- pose solutions in the case of a network with a grid structure. We compare three methods of self- organisation that are partly inspired by physical and biological phenomena. As an application, we envision sensor networks or any type of de- centralised system.
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https://hal.inria.fr/hal-02195799
Contributor : Nicolas Gauville <>
Submitted on : Friday, July 26, 2019 - 3:06:26 PM
Last modification on : Monday, August 24, 2020 - 4:33:12 PM

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  • HAL Id : hal-02195799, version 1

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Nicolas Gauville, Nazim Fatès, Irène Marcovici. Diagnostic décentralisé à l'aide d'automates cellulaires. JFSMA 2019 - 27emes Journées Francophones sur les Systèmes Multi-Agents, Institut de Recherche en informatique de Toulouse et l'Association française pour l'Intelligence Artificielle, Jul 2019, Toulouse, France. p. 96-105. ⟨hal-02195799⟩

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