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A fundamental question that shrouds the emergence of massively parallel computing (MPC) platforms is how can the additional power of the MPC paradigm be leveraged to achieve faster algorithms compared to classical parallel models such as…

Data Structures and Algorithms · Computer Science 2018-05-09 Sepehr Assadi , Xiaorui Sun , Omri Weinstein

We present time-efficient distributed algorithms for decomposing graphs with large edge or vertex connectivity into multiple spanning or dominating trees, respectively. As their primary applications, these decompositions allow us to achieve…

Data Structures and Algorithms · Computer Science 2013-11-22 Keren Censor-Hillel , Mohsen Ghaffari , Fabian Kuhn

In this work, a graph partitioning problem in a fixed number of connected components is considered. Given an undirected graph with costs on the edges, the problem consists of partitioning the set of nodes into a fixed number of subsets with…

Optimization and Control · Mathematics 2024-11-12 Mishelle Cordero , Andrés Miniguano-Trujillo , Diego Recalde , Ramiro Torres , Polo Vaca

The most commonly used method to tackle the graph partitioning problem in practice is the multilevel approach. During a coarsening phase, a multilevel graph partitioning algorithm reduces the graph size by iteratively contracting nodes and…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-03-26 Henning Meyerhenke , Peter Sanders , Christian Schulz

We present a distributed randomized algorithm finding Minimum Spanning Tree (MST) of a given graph in O(1) rounds, with high probability, in the Congested Clique model. The input graph in the Congested Clique model is a graph of n nodes,…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-01 Tomasz Jurdzinski , Krzysztof Nowicki

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

A maximum weighted matching for bipartite graphs $G=(A \cup B,E)$ can be found by using the algorithm of Edmonds and Karp with a Fibonacci Heap and a modified Dijkstra in $O(nm + n^2 \log{n})$ time where n is the number of nodes and m the…

Data Structures and Algorithms · Computer Science 2007-05-23 Daniel Etzold

In the cut-query model, the algorithm can access the input graph $G=(V,E)$ only via cut queries that report, given a set $S\subseteq V$, the total weight of edges crossing the cut between $S$ and $V\setminus S$. This model was introduced by…

Data Structures and Algorithms · Computer Science 2025-10-22 Yotam Kenneth-Mordoch , Robert Krauthgamer

Given a distributed network represented by a weighted undirected graph $G=(V,E)$ on $n$ vertices, and a parameter $k$, we devise a distributed algorithm that computes a routing scheme in $(n^{1/2+1/k}+D)\cdot n^{o(1)}$ rounds, where $D$ is…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-22 Michael Elkin , Ofer Neiman

We study random subgraphs of the 2-dimensional Hamming graph H(2,n), which is the Cartesian product of two complete graphs on $n$ vertices. Let $p$ be the edge probability, and write $p=\frac{1+\vep}{2(n-1)}$ for some $\vep\in \R$. In Borgs…

Probability · Mathematics 2008-12-15 Remco van der Hofstad , Malwina J. Luczak

In the Connected Dominating Set problem we are given a graph $G=(V,E)$ and seek a minimum size dominating set $S \subseteq V$ such that the subgraph $G[S]$ of $G$ induced by $S$ is connected. In the $2$-Edge-Connected Dominating Set problem…

Data Structures and Algorithms · Computer Science 2019-12-23 Amir Belgi , Zeev Nutov

In this paper we study the tradeoff between parallelism and communication cost in a map-reduce computation. For any problem that is not "embarrassingly parallel," the finer we partition the work of the reducers so that more parallelism can…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-06-21 Foto N. Afrati , Anish Das Sarma , Semih Salihoglu , Jeffrey D. Ullman

The cut-set $\partial(S)$ of a graph $G=(V,E)$ is the set of edges that have one endpoint in $S\subset V$ and the other endpoint in $V\setminus S$, and whenever $G[S]$ is connected, the cut $[S,V\setminus S]$ of $G$ is called a connected…

We show the first near-linear time randomized algorithms for listing all minimum vertex cuts of polylogarithmic size that separate the graph into at least three connected components (also known as shredders) and for finding the most…

Data Structures and Algorithms · Computer Science 2024-07-15 Kevin Hua , Daniel Li , Jaewoo Park , Thatchaphol Saranurak

The reassembling of a simple connected graph G = (V,E) is an abstraction of a problem arising in earlier studies of network analysis. Its simplest formulation is in two steps: (1) We cut every edge of G into two halves, thus obtaining a…

Discrete Mathematics · Computer Science 2016-04-27 Assaf Kfoury , Saber Mirzaei

In this paper we study the problem of maintaining the strongly connected components of a graph in the presence of failures. In particular, we show that given a directed graph $G=(V,E)$ with $n=|V|$ and $m=|E|$, and an integer value $k\geq…

Data Structures and Algorithms · Computer Science 2017-04-25 Surender Baswana , Keerti Choudhary , Liam Roditty

If we pick $n$ random points uniformly in $[0,1]^d$ and connect each point to its $k-$nearest neighbors, then it is well known that there exists a giant connected component with high probability. We prove that in $[0,1]^d$ it suffices to…

Combinatorics · Mathematics 2017-11-15 George C. Linderman , Gal Mishne , Yuval Kluger , Stefan Steinerberger

The nearest lattice point problem in $\mathbb{R}^n$ is formulated in a distributed network with $n$ nodes. The objective is to minimize the probability that an incorrect lattice point is found, subject to a constraint on inter-node…

Information Theory · Computer Science 2024-09-17 V. A. Vaishampayan , M. F. Bollauf

The theme of this paper is how to find all instances of a given "sample" graph in a larger "data graph," using a single round of map-reduce. For the simplest sample graph, the triangle, we improve upon the best known such algorithm. We then…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-11-22 Foto N. Afrati , Dimitris Fotakis , Jeffrey D. Ullman

For a graph G=(V,E), finding a set of disjoint edges that do not share any vertices is called a matching problem, and finding the maximum matching is a fundamental problem in the theory of distributed graph algorithms. Although local…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-03-14 Naoki Kitamura , Taisuke Izumi