Lower Bounds for Maximal Matchings and Maximal Independent Sets

Author:

Balliu Alkida1,Brandt Sebastian2,Hirvonen Juho3,Olivetti Dennis1,Rabie Mikaël4,Suomela Jukka3

Affiliation:

1. Aalto University, Finland and University of Freiburg, Freiburg im Breisgau, Germany

2. ETH Zurich, Zurich, Switzerland

3. Aalto University, Aalto, Finland

4. Aalto University, Finland and Université de Paris, Paris, France

Abstract

There are distributed graph algorithms for finding maximal matchings and maximal independent sets in O ( Δ + log * n ) communication rounds; here, n is the number of nodes and Δ is the maximum degree. The lower bound by Linial (1987, 1992) shows that the dependency on n is optimal: These problems cannot be solved in o (log * n ) rounds even if Δ = 2. However, the dependency on Δ is a long-standing open question, and there is currently an exponential gap between the upper and lower bounds. We prove that the upper bounds are tight. We show that any algorithm that finds a maximal matching or maximal independent set with probability at least 1-1/ n requires Ω (min { Δ , log log n / log log log n }) rounds in the LOCAL model of distributed computing. As a corollary, it follows that any deterministic algorithm that finds a maximal matching or maximal independent set requires Ω (min { Δ , log n / log log n }) rounds; this is an improvement over prior lower bounds also as a function of  n .

Funder

Academy of Finland

ESTATE

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Hardware and Architecture,Information Systems,Control and Systems Engineering,Software

Reference43 articles.

1. A fast and simple randomized parallel algorithm for the maximal independent set problem

2. Alkida Balliu Sebastian Brandt Yuval Efron Juho Hirvonen Yannic Maus Dennis Olivetti and Jukka Suomela. 2019. Classification of distributed binary labeling problems. In Proceedings of the 34th International Symposium on Distributed Computing 2020 October 12-16 2020 . 17:1–17:17. DOI:10.4230/LIPIcs.DISC.2020.17

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