The @math -coloring problem is a fundamental symmetry breaking problem in distributed computing. We give a new randomized coloring algorithm for @math -coloring running in @math rounds with probability @math in a graph with @math nodes and maximum degree @math . This implies that the @math -coloring problem is easier than the maximal independent set problem and the maximal matching problem, due to their lower bounds by Kuhn, Moscibroda, and Wattenhofer [PODC'04]. Our algorithm also extends to the list-coloring problem where the palette of each node contains @math colors.
More efficient algorithms for @math -coloring exist for very dense graphs, e.g. a deterministic O( @math ) algorithm for growth bounded graphs (e.g. unit disk graphs) @cite_0 , as well as for many types of sparse graphs @cite_51 @cite_44 @cite_2 , e.g. for graphs of low arboricity. @cite_44 described a @math -coloring algorithm for locally-sparse graphs. We will extend this result to cover list-colorings as well.
@cite_0 @cite_44 @cite_51 @cite_2
2294368603 2797253418 2023634316 2157562188
Graph coloring is a central problem in distributed computing. Both vertex- and edge-coloring problems have been extensively studied in this context. In this paper we show that a (2Δ − 1)-edge-coloring can be computed in time smaller than loge n for any e > 0, specifically, in eO([EQUATION]log log n) rounds. This establishes a separation between the (2Δ − 1)-edge-coloring and Maximal Matching problems, as the latter is known to require Ω([EQUATION]log n) time [15]. No such separation is currently known between the (Δ + 1)-vertex-coloring and Maximal Independent Set problems. We devise a (1 + e)Δ-edge-coloring algorithm for an arbitrarily small constant e > 0. This result applies whenever Δ ≥ Δe, for some constant Δe which depends on e. The running time of this algorithm is O(log* Δ + [EQUATION]). A much earlier logarithmic-time algorithm by Dubhashi, Grable and Panconesi [11] assumed Δ ≥ (log n)1+Ω(1). For Δ = (log n)1+Ω(1) the running time of our algorithm is only O(log* n). This constitutes a drastic improvement of the previous logarithmic bound [11, 9]. Our results for (2Δ − 1)-edge-coloring also follows from our more general results concerning (1 − e)-locally sparse graphs. Specifically, we devise a (Δ + 1)-vertex coloring algorithm for (1 − e)-locally sparse graphs that runs in O(log* Δ + log(1 e)) rounds for any e > 0, provided that eΔ = (log n)1+Ω(1). We conclude that the (Δ + 1)-vertex coloring problem for (1 − e)-locally sparse graphs can be solved in O(log(1 e)) + eO([EQUATION]log log n) time. This imply our result about (2Δ − 1)-edge-coloring, because (2Δ − 1)-edge-coloring reduces to (Δ + 1)-vertex-coloring of the line graph of the original graph, and because line graphs are (1 2 + o(1))-locally sparse. We give a new randomized distributed algorithm for (Δ +1)-coloring in the LOCAL model, running in O(s log Δ)+ 2O(slog log n) rounds in a graph of maximum degree Δ. This implies that the (Δ +1)-coloring problem is easier than the maximal independent set problem and the maximal matching problem, due to their lower bounds of Ω(min(sflog n log log n, flog Δ log log Δ)) by Kuhn, Moscibroda, and Wattenhofer [PODC’04]. Our algorithm also extends to list-coloring where the palette of each node contains Δ +1 colors. We extend the set of distributed symmetry-breaking techniques by performing a decomposition of graphs into dense and sparse parts. We deterministically compute a @D+1 coloring and a maximal independent set(MIS) in time O(@D^1^ ^2^+^@Q^(^1^ ^h^)+log^*n) for @D"1"+"[email protected][email protected]^1^+^i^ ^h, where @D"j is defined as the maximal number of nodes within distance j for a node and @D:[email protected]"1. Our greedy coloring and MIS algorithms improve the state-of-the-art algorithms running in O(@D+log^*n) for a large class of graphs, i.e., graphs of (moderate) neighborhood growth with h>=36. We also state and analyze a randomized coloring algorithm in terms of the chromatic number, the run time and the used colors. Our algorithm runs in time O([email protected]+log^*n) for @[email protected][email protected](log^1^+^1^ ^l^o^g^^^*^nn) and @[email protected]?O(@D log^1^+^1^ ^l^o^g^^^*^nn). For graphs of polylogarithmic chromatic number the analysis reveals an exponential gap compared to the fastest @D+1 coloring algorithm running in time O([email protected]+logn). The algorithm works without knowledge of @g and uses less than @D colors, i.e., (1-1 O(@g))@D with high probability. To the best of our knowledge this is the first distributed algorithm for (such) general graphs taking the chromatic number @g into account. We also improve on the state of the art deterministic computation of (2,c)-ruling sets. We study deterministic, distributed algorithms for two weak variants of the standard graph coloring problem. We consider defective colorings, i.e., colorings where nodes of a color class may induce a graph of maximum degree d for some parameter d>0. We also look at colorings where a minimum number of multi-chromatic edges is required. For an integer k>0, we call a coloring k-partially proper if every node v has at least min k,deg(v) neighbors with a different color. We show that for all d∈ 1,...,Δ , it is possible to compute a O(Δ2 d2)-coloring with defect d in time O(log*n) where Δ is the largest degree of the network graph. Similarly, for all k∈ 1,...,Δ , a k-partially proper O(k2)-coloring can be computed in O(log*n) rounds. As an application of our weak defective coloring algorithm, we obtain a faster deterministic algorithm for the standard vertex coloring problem on graphs with moderate degrees. We show that in time O(Δ+log*n), a (Δ+1)-coloring can be computed, a task for which the best previous algorithm required time O(Δ*log(Δ) + log*n). The same result holds for the problem of computing a maximal independent set.