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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 study graph realization problems from a distributed perspective and we study it in the node capacitated clique (NCC) model of distributed computing, recently introduced for representing peer-to-peer networks. We focus on two central…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-02-19 John Augustine , Keerti Choudhary , Avi Cohen , David Peleg , Sumathi Sivasubramaniam , Suman Sourav

This paper improves and in two cases nearly settles, up to logarithmically lower-order factors, the deterministic complexity of some of the most central problems in distributed graph algorithms, which have been studied for over three…

Data Structures and Algorithms · Computer Science 2024-10-28 Mohsen Ghaffari , Christoph Grunau

The paper considers the SUPPORTED model of distributed computing introduced by Schmid and Suomela [HotSDN'13], generalizing the LOCAL and CONGEST models. In this framework, multiple instances of the same problem, differing from each other…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-01-02 Akanksha Agrawal , John Augustine , David Peleg , Srikkanth Ramachandran

Graph coloring problems are among the most fundamental problems in parallel and distributed computing, and have been studied extensively in both settings. In this context, designing efficient deterministic algorithms for these problems has…

Data Structures and Algorithms · Computer Science 2024-04-26 Sam Coy , Artur Czumaj , Peter Davies , Gopinath Mishra

In the distributed backup-placement problem each node of a network has to select one neighbor, such that the maximum number of nodes that make the same selection is minimized. This is a natural relaxation of the perfect matching problem, in…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-19 Leonid Barenboim , Gal Oren

Online algorithms make decisions based on past inputs. In general, the decision may depend on the entire history of inputs. If many computers run the same online algorithm with the same input stream but are started at different times, they…

Data Structures and Algorithms · Computer Science 2022-10-14 Maciej Pacut , Mahmoud Parham , Joel Rybicki , Stefan Schmid , Jukka Suomela , Aleksandr Tereshchenko

We show how to construct an overlay network of constant degree and diameter $O(\log n)$ in time $O(\log n)$ starting from an arbitrary weakly connected graph. We assume a synchronous communication network in which nodes can send messages to…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-07-28 Thorsten Götte , Kristian Hinnenthal , Christian Scheideler , Julian Werthmann

$ \renewcommand{\tilde}{\widetilde} $We present an $\tilde{O}(\log^2 n)$ round deterministic distributed algorithm for the maximal independent set problem. By known reductions, this round complexity extends also to maximal matching,…

Data Structures and Algorithms · Computer Science 2023-03-29 Mohsen Ghaffari , Christoph Grunau

We present a new, simple, algorithm for the local vertex connectivity problem (LocalVC) introduced by Nanongkai~et~al. [STOC'19]. Roughly, given an undirected unweighted graph $G$, a seed vertex $x$, a target volume $\nu$, and a target…

Data Structures and Algorithms · Computer Science 2019-07-09 Danupon Nanongkai , Thatchaphol Saranurak , Sorrachai Yingchareonthawornchai

The congested clique model is a message-passing model of distributed computation where the underlying communication network is the complete graph of $n$ nodes. In this paper we consider the situation where the joint input to the nodes is an…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-06-13 Pedro Montealegre , Sebastian Perez-Salazar , Ivan Rapaport , Ioan Todinca

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

We consider the Backup Placement problem in networks in the $\mathcal{CONGEST}$ distributed setting. Given a network graph $G = (V,E)$, the goal of each vertex $v \in V$ is selecting a neighbor, such that the maximum number of vertices in…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-16 Leonid Barenboim , Gal Oren

In computer networks, participants may cooperate in processing tasks, so that loads are balanced among them. We present local distributed algorithms that (repeatedly) use local imbalance criteria to transfer loads concurrently across the…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-07 Yefim Dinitz , Shlomi Dolev , Manish Kumar

This paper addresses the cornerstone family of \emph{local problems} in distributed computing, and investigates the curious gap between randomized and deterministic solutions under bandwidth restrictions. Our main contribution is in…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-08-09 Keren Censor-Hillel , Merav Parter , Gregory Schwartzman

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

In this paper we consider a network of processors aiming at cooperatively solving linear programming problems subject to uncertainty. Each node only knows a common cost function and its local uncertain constraint set. We propose a…

Optimization and Control · Mathematics 2019-08-27 Mohammadreza Chamanbaz , Giuseppe Notarstefano , Roland Bouffanais

We consider a class of popular distributed non-convex optimization problems, in which agents connected by a network $\mathcal{G}$ collectively optimize a sum of smooth (possibly non-convex) local objective functions. We address the…

Optimization and Control · Mathematics 2020-01-08 Haoran Sun , Mingyi Hong

We consider coloring problems in the distributed message-passing setting. The previously-known deterministic algorithms for edge-coloring employed at least (2Delta - 1) colors, even though any graph admits an edge-coloring with Delta + 1…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-10-24 Leonid Barenboim , Michael Elkin , Tzalik Maimon

Many combinatorial optimization problems can be approximated within $(1 \pm \epsilon)$ factors in $\text{poly}(\log n, 1/\epsilon)$ rounds in the LOCAL model via network decompositions [Ghaffari, Kuhn, and Maus, STOC 2018]. These approaches…

Data Structures and Algorithms · Computer Science 2025-10-24 Yi-Jun Chang , Hsin-Hao Su
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