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The Locality of Distributed Symmetry Breaking

The locality of distributed symmetry breaking
Authors: Leonid Barenboim; Michael Elkin; Seth Pettie; Johannes Schneider 0002;

The Locality of Distributed Symmetry Breaking

Abstract

Symmetry-breaking problems are among the most well studied in the field of distributed computing and yet the most fundamental questions about their complexity remain open. In this article we work in the LOCAL model (where the input graph and underlying distributed network are identical) and study the randomized complexity of four fundamental symmetry-breaking problems on graphs: computing MISs (maximal independent sets), maximal matchings, vertex colorings, and ruling sets. A small sample of our results includes the following: —An MIS algorithm running in O (log 2 Δ + 2 o (√log log n ) ) time, where Δ is the maximum degree. This is the first MIS algorithm to improve on the 1986 algorithms of Luby and Alon, Babai, and Itai, when log n ≪ Δ ≪ 2√log n , and comes close to the Ω(log Δ / log log Δ lower bound of Kuhn, Moscibroda, and Wattenhofer. —A maximal matching algorithm running in O (log Δ + log 4 log n ) time. This is the first significant improvement to the 1986 algorithm of Israeli and Itai. Moreover, its dependence on Δ is nearly optimal . —A (Δ + 1)-coloring algorithm requiring O (log Δ + 2 o (√log log n ) time, improving on an O (log Δ + √log n )-time algorithm of Schneider and Wattenhofer. —A method for reducing symmetry-breaking problems in low arboricity/degeneracy graphs to low-degree graphs. (Roughly speaking, the arboricity or degeneracy of a graph bounds the density of any subgraph.) Corollaries of this reduction include an O (√log n )-time maximal matching algorithm for graphs with arboricity up to 2√log n and an O (log 2/3 n )-time MIS algorithm for graphs with arboricity up to 2 (log n )1/3 . Each of our algorithms is based on a simple but powerful technique for reducing a randomized symmetry-breaking task to a corresponding deterministic one on a poly(log n )-size graph.

Keywords

FOS: Computer and information sciences, F.2.2; G.2.2, matching, MIS, G.2.2, Distributed systems, Coloring of graphs and hypergraphs, Computer Science - Distributed, Parallel, and Cluster Computing, Edge subsets with special properties (factorization, matching, partitioning, covering and packing, etc.), vertex coloring, Graph theory (including graph drawing) in computer science, Distributed, Parallel, and Cluster Computing (cs.DC), F.2.2, distributed networks

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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
159
Top 1%
Top 1%
Top 10%
Green
bronze