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Related papers: Local Distributed Rounding: Generalized to MIS, Ma…

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We consider the problem of designing deterministic graph algorithms for the model of Massively Parallel Computation (MPC) that improve with the sparsity of the input graph, as measured by the notion of arboricity. For the problems of…

Data Structures and Algorithms · Computer Science 2023-07-03 Manuela Fischer , Jeff Giliberti , Christoph Grunau

Graph coloring is fundamental to distributed computing. We give the first sub-logarithmic distributed algorithm for coloring cluster graphs. These graphs are obtained from the underlying communication network by contracting nodes and edges,…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-06-17 Maxime Flin , Magnus M. Halldorsson , Alexandre Nolin

It is a well known fact that sequential algorithms which exhibit a strong "local" nature can be adapted to the distributed setting given a legal graph coloring. The running time of the distributed algorithm will then be at least the number…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-05-15 Ken-ichi Kawarabayashi , Gregory Schwartzman

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 obtain improved distributed algorithms in the CONGEST message-passing setting for problems on power graphs of an input graph $G$. This includes Coloring, Maximal Independent Set, and related problems. We develop a general deterministic…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-08-14 Leonid Barenboim , Uri Goldenberg

One of the most basic techniques in algorithm design consists of breaking a problem into subproblems and then proceeding recursively. In the case of graph algorithms, one way to implement this approach is through separator sets. Given a…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-13 Benjamin Jauregui , Pedro Montealegre , Ivan Rapaport

We present a simple polylogarithmic-time deterministic distributed algorithm for network decomposition. This improves on a celebrated $2^{O(\sqrt{\log n})}$-time algorithm of Panconesi and Srinivasan [STOC'92] and settles a central and…

Data Structures and Algorithms · Computer Science 2020-05-12 Václav Rozhoň , Mohsen Ghaffari

Distributed graph algorithms that separately optimize for either the number of rounds used or the total number of messages sent have been studied extensively. However, algorithms simultaneously efficient with respect to both measures have…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-05-18 Bernhard Haeupler , D. Ellis Hershkowitz , David Wajc

The present paper studies local distributed graph problems in highly dynamic networks. Communication and changes of the graph happen in synchronous rounds and our algorithms always, i.e., in every round, satisfy non-trivial guarantees, no…

Data Structures and Algorithms · Computer Science 2018-12-10 Philipp Bamberger , Fabian Kuhn , Yannic Maus

In the past few years, a successful line of research has lead to lower bounds for several fundamental local graph problems in the distributed setting. These results were obtained via a technique called round elimination. On a high level,…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-29 Alkida Balliu , Sebastian Brandt , Fabian Kuhn , Dennis Olivetti , Joonatan Saarhelo

We present randomized distributed algorithms for the maximal independent set problem (MIS) that, while keeping the time complexity nearly matching the best known, reduce the energy complexity substantially. These algorithms work in the…

Data Structures and Algorithms · Computer Science 2023-05-24 Mohsen Ghaffari , Julian Portmann

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 study the complexity of fundamental distributed graph problems in the recently popular setting where information about the input graph is available to the nodes before the start of the computation. We focus on the most common such…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-03 Alkida Balliu , Thomas Boudier , Sebastian Brandt , Dennis Olivetti

We present the first local problem that shows a super-constant separation between the classical randomized LOCAL model of distributed computing and its quantum counterpart. By prior work, such a separation was known only for an artificial…

The locality of a graph problem is the smallest distance $T$ such that each node can choose its own part of the solution based on its radius-$T$ neighborhood. In many settings, a graph problem can be solved efficiently with a distributed or…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-12-14 Yi-Jun Chang , Jan Studený , Jukka Suomela

In classic distributed graph problems, each instance on a graph specifies a space of feasible solutions (e.g. all proper ($\Delta+1$)-list-colorings of the graph), and the task of distributed algorithm is to construct a feasible solution…

Data Structures and Algorithms · Computer Science 2018-02-20 Weiming Feng , Yitong Yin

The distributed coloring problem is arguably one of the key problems studied in the area of distributed graph algorithms. The most standard variant of the problem asks for a proper vertex coloring of a graph with $\Delta+1$ colors, where…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-05 Marc Fuchs , Fabian Kuhn

We give a randomized $\Delta$-coloring algorithm in the LOCAL model that runs in $\text{poly} \log \log n$ rounds, where $n$ is the number of nodes of the input graph and $\Delta$ is its maximum degree. This means that randomized…

Data Structures and Algorithms · Computer Science 2022-11-15 Manuela Fischer , Yannic Maus , Magnús M. Halldórsson

The main goal in distributed symmetry-breaking is to understand the locality of problems; i.e., the radius of the neighborhood that a node needs to explore in order to arrive at its part of a global solution. In this work, we study the…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-23 Seri Khoury , Manish Purohit , Aaron Schild , Joshua Wang

We present a framework for deterministically rounding a dynamic fractional matching. Applying our framework in a black-box manner on top of existing fractional matching algorithms, we derive the following new results: (1) The first…

Data Structures and Algorithms · Computer Science 2021-05-05 Sayan Bhattacharya , Peter Kiss