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Optimal Space Lower Bound for Deterministic Self-Stabilizing Leader Election Algorithms.
- Source :
-
Discrete Mathematics & Theoretical Computer Science (DMTCS) . 2023, Vol. 25 Issue 1, p1-17. 17p. - Publication Year :
- 2023
-
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 (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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13658050
- Volume :
- 25
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Discrete Mathematics & Theoretical Computer Science (DMTCS)
- Publication Type :
- Academic Journal
- Accession number :
- 164893118