research-article

Self-stabilizing Systems in Spite of High Dynamics

Authors:

Karine Altisen,

Stéphane Devismes,

Colette Johnen,

Franck PetitAuthors Info & Claims

ICDCN '21: Proceedings of the 22nd International Conference on Distributed Computing and Networking

Pages 156 - 165

https://doi.org/10.1145/3427796.3427838

Published: 05 January 2021 Publication History

Abstract

We initiate research on self-stabilization in highly dynamic identified message passing systems where dynamics is modeled using time-varying graphs (TVGs). More precisely, we address the self-stabilizing leader election problem in three wide classes of TVGs: the class of TVGs with temporal diameter bounded by Δ, the class of TVGs with temporal diameter quasi-bounded by Δ, and the class of TVGs with recurrent connectivity only, where . We first study conditions under which our problem can be solved. We introduce the notion of size-ambiguity to show that the assumption on the knowledge of the number n of processes is central. Our results reveal that, despite the existence of unique process identifiers, any deterministic self-stabilizing leader election algorithm working in the class or cannot be size-ambiguous, justifying why our solutions for those classes assume the exact knowledge of n. We then present three self-stabilizing leader election algorithms for Classes, and, respectively. Our algorithm for stabilizes in at most 3Δ rounds. In and, stabilization time cannot be bounded, except for trivial specifications. However, we show that our solutions are speculative in the sense that their stabilization time in is O(Δ) rounds.

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Cited By

Aldrini JChihi ISidhom L(2024)Fault diagnosis and self-healing for smart manufacturing: a reviewJournal of Intelligent Manufacturing10.1007/s10845-023-02165-635:6(2441-2473)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10845-023-02165-6
Béduneau GJaber GDucourthial B(2022)A method for predicting ITS cooperative applications performancesComputer Networks10.1016/j.comnet.2022.109148216(109148)Online publication date: Oct-2022
https://doi.org/10.1016/j.comnet.2022.109148
Beduneau GJaber GDucourthial B(2021)Dynamic p-graphs for predictions in vehicular networks2021 17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)10.1109/WiMob52687.2021.9606303(407-410)Online publication date: 11-Oct-2021
https://doi.org/10.1109/WiMob52687.2021.9606303

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We initiate research on self-stabilization in highly dynamic identified message-passing systems where dynamics is modeled using time-varying graphs (TVGs). More precisely, we address the self-stabilizing leader election problem in three wide classes of ...
Self-stabilizing systems in spite of high dynamics
Abstract
We initiate research on self-stabilization in highly dynamic identified message-passing systems where dynamics is modeled using time-varying graphs (TVGs). More precisely, we address the self-stabilizing leader election problem in ...
Highlights
- We address the self-stabilizing leader election in highly dynamic systems modeled by time-varying graphs (TVGs).

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cover image ACM Other conferences

ICDCN '21: Proceedings of the 22nd International Conference on Distributed Computing and Networking

January 2021

252 pages

ISBN:9781450389334

DOI:10.1145/3427796

Copyright © 2021 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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Publication History

Published: 05 January 2021

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ICDCN '21

ICDCN '21: International Conference on Distributed Computing and Networking 2021

January 5 - 8, 2021

Nara, Japan

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Cited By

Aldrini JChihi ISidhom L(2024)Fault diagnosis and self-healing for smart manufacturing: a reviewJournal of Intelligent Manufacturing10.1007/s10845-023-02165-635:6(2441-2473)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10845-023-02165-6
Béduneau GJaber GDucourthial B(2022)A method for predicting ITS cooperative applications performancesComputer Networks10.1016/j.comnet.2022.109148216(109148)Online publication date: Oct-2022
https://doi.org/10.1016/j.comnet.2022.109148
Beduneau GJaber GDucourthial B(2021)Dynamic p-graphs for predictions in vehicular networks2021 17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)10.1109/WiMob52687.2021.9606303(407-410)Online publication date: 11-Oct-2021
https://doi.org/10.1109/WiMob52687.2021.9606303

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