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One of the fundamental open problems in the area of distributed graph algorithms is the question of whether randomization is needed for efficient symmetry breaking. While there are fast, $\text{poly}\log n$-time randomized distributed…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-05-29 Philipp Bamberger , Mohsen Ghaffari , Fabian Kuhn , Yannic Maus , Jara Uitto

In the Colored Clustering problem, one is asked to cluster edge-colored (hyper-)graphs whose colors represent interaction types. More specifically, the goal is to select as many edges as possible without choosing two edges that share an…

Data Structures and Algorithms · Computer Science 2023-02-02 Leon Kellerhals , Tomohiro Koana , Pascal Kunz , Rolf Niedermeier

We present ${\rm poly\log\log n}$-round randomized distributed algorithms to compute vertex splittings, a partition of the vertices of a graph into $k$ parts such that a node of degree $d(u)$ has $\approx d(u)/k$ neighbors in each part. Our…

Data Structures and Algorithms · Computer Science 2022-08-18 Magnús M. Halldórsson , Yannic Maus , Alexandre Nolin

Locally finding a solution to symmetry-breaking tasks such as vertex-coloring, edge-coloring, maximal matching, maximal independent set, etc., is a long-standing challenge in distributed network computing. More recently, it has also become…

Data Structures and Algorithms · Computer Science 2017-02-03 Pierre Fraigniaud , Marc Heinrich , Adrian Kosowski

The celebrated palette sparsification result of [Assadi, Chen, and Khanna SODA'19] shows that to compute a $\Delta+1$ coloring of the graph, where $\Delta$ denotes the maximum degree, it suffices if each node limits its color choice to…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-04-13 Maxime Flin , Mohsen Ghaffari , Magnús M. Halldórsson , Fabian Kuhn , Alexandre Nolin

In this work, we present a fast distributed algorithm for local potential problems: these are graph problems where the task is to find a locally optimal solution where no node can unilaterally improve the utility in its local neighborhood…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-20 Alkida Balliu , Thomas Boudier , Francesco d'Amore , Fabian Kuhn , Dennis Olivetti , Gustav Schmid , Jukka Suomela

We settle the complexity of the $(\Delta+1)$-coloring and $(\Delta+1)$-list coloring problems in the CONGESTED CLIQUE model by presenting a simple deterministic algorithm for both problems running in a constant number of rounds. This…

Data Structures and Algorithms · Computer Science 2020-09-15 Artur Czumaj , Peter Davies , Merav Parter

We develop an algorithmic framework for graph colouring that reduces the problem to verifying a local probabilistic property of the independent sets. With this we give, for any fixed $k\ge 3$ and $\varepsilon>0$, a randomised…

Data Structures and Algorithms · Computer Science 2020-04-16 Ewan Davies , Ross J. Kang , François Pirot , Jean-Sébastien Sereni

We design fast dynamic algorithms for proper vertex and edge colorings in a graph undergoing edge insertions and deletions. In the static setting, there are simple linear time algorithms for $(\Delta+1)$- vertex coloring and…

Data Structures and Algorithms · Computer Science 2017-11-15 Sayan Bhattacharya , Deeparnab Chakrabarty , Monika Henzinger , Danupon Nanongkai

We study a family of closely-related distributed graph problems, which we call degree splitting, where roughly speaking the objective is to partition (or orient) the edges such that each node's degree is split almost uniformly. Our findings…

Data Structures and Algorithms · Computer Science 2016-08-11 Mohsen Ghaffari , Hsin-Hao Su

We present a randomized algorithm that, given a constant $\epsilon > 0$, outputs a proper $(1+\epsilon)\Delta$-edge-coloring of an $m$-edge simple graph $G$ of maximum degree $\Delta \geq 1/\epsilon$ in $O(m)$ time with high probability.…

Data Structures and Algorithms · Computer Science 2025-02-10 Anton Bernshteyn , Abhishek Dhawan

We give a new randomized distributed algorithm for the $\Delta+1$-list coloring problem. The algorithm and its analysis dramatically simplify the previous best result known of Chang, Li, and Pettie [SICOMP 2020]. This allows for numerous…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-05-12 Magnús M. Halldórsson , Alexandre Nolin , Tigran Tonoyan

We give deterministic distributed $(1+\epsilon)$-approximation algorithms for Minimum Vertex Coloring and Maximum Independent Set on chordal graphs in the LOCAL model. Our coloring algorithm runs in $O(\frac{1}{\epsilon} \log n)$ rounds,…

Data Structures and Algorithms · Computer Science 2018-05-15 Christian Konrad , Viktor Zamaraev

In the context of communication complexity, we explore protocols for graph coloring, focusing on the vertex and edge coloring problems in $n$-vertex graphs $G$ with a maximum degree $\Delta$. We consider a scenario where the edges of $G$…

Data Structures and Algorithms · Computer Science 2025-05-12 Yi-Jun Chang , Gopinath Mishra , Hung Thuan Nguyen , Farrel D Salim

We present a new approach to randomized distributed graph coloring that is simpler and more efficient than previous ones. In particular, it allows us to tackle the $(\operatorname{deg}+1)$-list-coloring (D1LC) problem, where each node $v$…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-12-02 Magnús M. Halldórsson , Fabian Kuhn , Alexandre Nolin , Tigran Tonoyan

Let $\epsilon \in (0, 1)$ and $n, \Delta \in \mathbb N$ be such that $\Delta = \Omega\left(\max\left\{\frac{\log n}{\epsilon},\, \left(\frac{1}{\epsilon}\log \frac{1}{\epsilon}\right)^2\right\}\right)$. Given an $n$-vertex $m$-edge simple…

Data Structures and Algorithms · Computer Science 2025-02-14 Abhishek Dhawan

We present new randomized algorithms that improve the complexity of the classic $(\Delta+1)$-coloring problem, and its generalization $(\Delta+1)$-list-coloring, in three well-studied models of distributed, parallel, and centralized…

Data Structures and Algorithms · Computer Science 2018-11-06 Yi-Jun Chang , Manuela Fischer , Mohsen Ghaffari , Jara Uitto , Yufan Zheng

Locally Checkable Labeling (LCL) problems include essentially all the classic problems of $\mathsf{LOCAL}$ distributed algorithms. In a recent enlightening revelation, Chang and Pettie [arXiv 1704.06297] showed that any LCL (on bounded…

Data Structures and Algorithms · Computer Science 2017-05-17 Manuela Fischer , Mohsen Ghaffari

We show that any randomised Monte Carlo distributed algorithm for the Lov\'asz local lemma requires $\Omega(\log \log n)$ communication rounds, assuming that it finds a correct assignment with high probability. Our result holds even in the…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-11-04 Sebastian Brandt , Orr Fischer , Juho Hirvonen , Barbara Keller , Tuomo Lempiäinen , Joel Rybicki , Jukka Suomela , Jara Uitto

In this paper we present a deterministic CONGEST algorithm to compute an $O(k\Delta)$-vertex coloring in $O(\Delta/k)+\log^* n$ rounds, where $\Delta$ is the maximum degree of the network graph and $1\leq k\leq O(\Delta)$ can be freely…

Data Structures and Algorithms · Computer Science 2023-02-28 Yannic Maus