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  1. Home > Articles & Issues >
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  3. Optimal Space Lower ...
Article

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

Lélia Blin, Laurent Feuilloley, Gabriel Le Bouder
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Submitted on
April 12, 2022
Accepted on
February 13, 2023
Published on
March 1, 2023
Last modified on
March 27, 2025
Volume 25
vol. 25:1
Distributed Computing and Networking
DOI
10.46298/dmtcs.9335
License
arXiv.org - Non-exclusive license to distribute
Graph Reconfiguration
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Optimal Space Lower Bound for Deterministic Self-Stabilizing Leader Election Algorithms

Lélia Blin, Laurent Feuilloley, Gabriel Le Bouder
Abstract
Given a boolean predicate $\Pi$ on labeled networks (e.g., proper coloring, leader election, etc.), a self-stabilizing algorithm for $\Pi$ 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 $\Pi$. 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 $\Omega(\log \log n)$-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. Comment: Final journal version for DMTCS (Conference version at OPODIS 2021)
Keywords
  • Computer Science - Distributed, Parallel, and Cluster Computing
  • Computer Science - Data Structures and Algorithms
Mathematics Subject Classification 2020
  • 05C15 - Coloring of graphs and hypergraphs
  • 05C82 - Small world graphs, complex networks (graph-theoretic aspects)
  • 68M14 - Distributed systems
  • 68Mxx - Computer system organization
  • 68Q17 - Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.)
  • 68R10 - Graph theory (including graph drawing) in computer science
  • 68W15 - Distributed algorithms
Cited by

Source: OpenCitations

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  • Optimal Memory Requirement for Self-stabilizing Token Circulation

    Authors : Lélia Blin ORCID, Gabriel Le Bouder, Franck Petit ORCID

    Journal reference : Volume , 2024, pp. 101-118

    DOI : 10.1007/978-3-031-60603-8_6
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