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The Complexity of Distributed Edge Coloring with Small Palettes

14 August 2017
Yi-Jun Chang
Qizheng He
Wenzheng Li
Seth Pettie
Jara Uitto
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Abstract

The complexity of distributed edge coloring depends heavily on the palette size as a function of the maximum degree Δ\DeltaΔ. In this paper we explore the complexity of edge coloring in the LOCAL model in different palette size regimes. 1. We simplify the \emph{round elimination} technique of Brandt et al. and prove that (2Δ−2)(2\Delta-2)(2Δ−2)-edge coloring requires Ω(log⁡Δlog⁡n)\Omega(\log_\Delta \log n)Ω(logΔ​logn) time w.h.p. and Ω(log⁡Δn)\Omega(\log_\Delta n)Ω(logΔ​n) time deterministically, even on trees. The simplified technique is based on two ideas: the notion of an irregular running time and some general observations that transform weak lower bounds into stronger ones. 2. We give a randomized edge coloring algorithm that can use palette sizes as small as Δ+O~(Δ)\Delta + \tilde{O}(\sqrt{\Delta})Δ+O~(Δ​), which is a natural barrier for randomized approaches. The running time of the algorithm is at most O(log⁡Δ⋅TLLL)O(\log\Delta \cdot T_{LLL})O(logΔ⋅TLLL​), where TLLLT_{LLL}TLLL​ is the complexity of a permissive version of the constructive Lovasz local lemma. 3. We develop a new distributed Lovasz local lemma algorithm for tree-structured dependency graphs, which leads to a (1+ϵ)Δ(1+\epsilon)\Delta(1+ϵ)Δ-edge coloring algorithm for trees running in O(log⁡log⁡n)O(\log\log n)O(loglogn) time. This algorithm arises from two new results: a deterministic O(log⁡n)O(\log n)O(logn)-time LLL algorithm for tree-structured instances, and a randomized O(log⁡log⁡n)O(\log\log n)O(loglogn)-time graph shattering method for breaking the dependency graph into independent O(log⁡n)O(\log n)O(logn)-size LLL instances. 4. A natural approach to computing (Δ+1)(\Delta+1)(Δ+1)-edge colorings (Vizing's theorem) is to extend partial colorings by iteratively re-coloring parts of the graph. We prove that this approach may be viable, but in the worst case requires recoloring subgraphs of diameter Ω(Δlog⁡n)\Omega(\Delta\log n)Ω(Δlogn). This stands in contrast to distributed algorithms for Brooks' theorem, which exploit the existence of O(log⁡Δn)O(\log_\Delta n)O(logΔ​n)-length augmenting paths.

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