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Optimal Space Lower Bound for Deterministic Self-Stabilizing Leader Election Algorithms

Authors Lélia Blin , Laurent Feuilloley , Gabriel Le Bouder

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Subject Classification

ACM Subject Classification
  • Theory of computation → Distributed computing models
Keywords
  • Space lower bound
  • memory tight bound
  • self-stabilization
  • leader election
  • anonymous
  • identifiers
  • state model
  • ring topology

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Abstract

Given a boolean predicate Π on labeled networks (e.g., proper coloring, leader election, etc.), a self-stabilizing algorithm for Π is a distributed algorithm that can start from any initial configuration of the network (i.e., every node has an arbitrary value assigned to each of its variables), and eventually converge to a configuration satisfying Π. It is known that leader election does not have a deterministic self-stabilizing algorithm using a constant-size register at each node, i.e., for some networks, some of their nodes must have registers whose sizes grow with the size n of the networks. On the other hand, it is also known that leader election can be solved by a deterministic self-stabilizing algorithm using registers of O(log log n) bits per node in any n-node bounded-degree network. We show that this latter space complexity is optimal. Specifically, we prove that every deterministic self-stabilizing algorithm solving leader election must use Ω(log log n)-bit per node registers in some n-node networks. In addition, we show that our lower bounds go beyond leader election, and apply to all problems that cannot be solved by anonymous algorithms.

Cite As Get BibTex

Lélia Blin, Laurent Feuilloley, and Gabriel Le Bouder. Optimal Space Lower Bound for Deterministic Self-Stabilizing Leader Election Algorithms. In 25th International Conference on Principles of Distributed Systems (OPODIS 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 217, pp. 24:1-24:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022) https://doi.org/10.4230/LIPIcs.OPODIS.2021.24

Author Details

Lélia Blin
  • Sorbonne Université, Université d’Evry-Val-d’Essonne, CNRS, LIP6 UMR 7606, 4 place Jussieu, 75005 Paris, France
Laurent Feuilloley
  • Univ. Lyon, Université Lyon 1, LIRIS UMR CNRS 5205, F-69621, Lyon, France
Gabriel Le Bouder
  • Sorbonne Université, CNRS, INRIA, LIP6 UMR 7606, 4 place Jussieu, 75005 Paris, France

Funding

Support by ANR ESTATE (ANR-16-CE25-0009-03) and ANR GrR (ANR-18-CE40-0032).

Acknowledgements

We thank the reviewers for their useful comments.

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