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Related papers: Congestion-Free Rerouting of Flows on DAGs

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The interconnection network is a key element in High-Performance Computing (HPC) and Datacenter (DC) systems whose performance depends on several design parameters, such as the topology, the switch architecture, and the routing algorithm.…

Networking and Internet Architecture · Computer Science 2025-02-04 Jose Rocher-Gonzalez , Jesus Escudero-Sahuquillo , Pedro J. Garcia , Francisco J. Quiles , Gaspar Mora

There has been intensive work on the parameterized complexity of the typically NP-hard task to edit undirected graphs into graphs fulfilling certain given vertex degree constraints. In this work, we lift the investigations to the case of…

Discrete Mathematics · Computer Science 2018-02-01 Robert Bredereck , Vincent Froese , Marcel Koseler , Marcelo Garlet Millani , André Nichterlein , Rolf Niedermeier

Carrier-grade networks comprise several layers where different protocols coexist. Nowadays, most of these networks have different control planes to manage routing on different layers, leading to a suboptimal use of the network resources and…

Networking and Internet Architecture · Computer Science 2016-11-17 Mohamed Lamine Lamali , Nasreddine Fergani , Johanne Cohen , Hélia Pouyllau

Coflow is a recently proposed networking abstraction to help improve the communication performance of data-parallel computing jobs. In multi-stage jobs, each job consists of multiple coflows and is represented by a Directed Acyclic Graph…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-12-22 Xin Wang , Hong Shen

Funnels are a new natural subclass of DAGs. Intuitively, a DAG is a funnel if every source-sink path can be uniquely identified by one of its arcs. Funnels are an analog to trees for directed graphs that is more restrictive than DAGs but…

Data Structures and Algorithms · Computer Science 2018-02-01 Marcelo Garlet Millani , Hendrik Molter , Rolf Niedermeier , Manuel Sorge

In this paper we study flow problems on temporal networks, where edge capacities and travel times change over time. We consider a network with $n$ nodes and $m$ edges where the capacity and length of each edge is a piecewise constant…

Data Structures and Algorithms · Computer Science 2025-02-20 Kristin Sheridan , Shuchi Chawla

Directed acyclic graphs (DAGs) are directed graphs in which there is no path from a vertex to itself. DAGs are an omnipresent data structure in computer science and the problem of counting the DAGs of given number of vertices and to sample…

Discrete Mathematics · Computer Science 2025-10-03 Martin Pépin , Alfredo Viola

Traffic forecasting is important for the success of intelligent transportation systems. Deep learning models, including convolution neural networks and recurrent neural networks, have been extensively applied in traffic forecasting problems…

Machine Learning · Computer Science 2022-07-08 Weiwei Jiang , Jiayun Luo

Finding a shortest path in a graph is one of the most classic problems in algorithmic and graph theory. While we dispose of quite efficient algorithms for this ordinary problem (like the Dijkstra or Bellman-Ford algorithms), some slight…

Data Structures and Algorithms · Computer Science 2024-08-05 Abderrahim Bendahi , Adrien Fradin

Modern generations of field-programmable gate arrays (FPGAs) allow for partial reconfiguration. In an online context, where the sequence of modules to be loaded on the FPGA is unknown beforehand, repeated insertion and deletion of modules…

Hardware Architecture · Computer Science 2007-05-23 Jan van der Veen , Sandor P. Fekete , Ali Ahmadinia , Christophe Bobda , Frank Hannig , Juergen Teich

We introduce the notion of a network's conduciveness, a probabilistically interpretable measure of how the network's structure allows it to be conducive to roaming agents, in certain conditions, from one portion of the network to another.…

Statistical Mechanics · Physics 2010-07-12 Valmir C. Barbosa

Graph-structured data ubiquitously appears in science and engineering. Graph neural networks (GNNs) are designed to exploit the relational inductive bias exhibited in graphs; they have been shown to outperform other forms of neural networks…

Machine Learning · Computer Science 2021-02-03 Veronika Thost , Jie Chen

Estimating the structure of directed acyclic graphs (DAGs) of features (variables) plays a vital role in revealing the latent data generation process and providing causal insights in various applications. Although there have been many…

Machine Learning · Computer Science 2024-03-06 Shaohua Fan , Shuyang Zhang , Xiao Wang , Chuan Shi

We study the single pair capacitated network design problem and the budget constrained max flow problem on undirected series-parallel graphs. These problems were well studied on directed series-parallel graphs, but little is known in the…

Data Structures and Algorithms · Computer Science 2024-01-22 Ishan Bansal , Ryan Mao , Avhan Mishra

With the widespread use of shared-nothing clusters of servers, there has been a proliferation of distributed object stores that offer high availability, reliability and enhanced performance for MapReduce-style workloads. However, relational…

Databases · Computer Science 2013-12-03 Lukasz Golab , Marios Hadjieleftheriou , Howard Karloff , Barna Saha

Renormalisation group (RG) methods provide one of the most important techniques for analysing the physics of many-body systems, both analytically and numerically. By iterating an RG map, which "course-grains" the description of a many-body…

Quantum Physics · Physics 2022-12-26 James D. Watson , Emilio Onorati , Toby S. Cubitt

The Shortest Path Reconfiguration problem has as input a graph G (with unit edge lengths) with vertices s and t, and two shortest st-paths P and Q. The question is whether there exists a sequence of shortest st-paths that starts with P and…

Computational Complexity · Computer Science 2012-04-26 Paul Bonsma

The reconfiguration problem for homomorphisms of digraphs to a reflexive digraph cycle, which amounts to deciding if a `reconfiguration graph' is connected, is known to by polynomially time solvable via a greedy algorithm based on certain…

Combinatorics · Mathematics 2025-03-19 David Emmanuel Pazmiño Pullas , Mark Siggers

Optimal power flow (OPF) is a critical optimization problem that allocates power to the generators in order to satisfy the demand at a minimum cost. Solving this problem exactly is computationally infeasible in the general case. In this…

Systems and Control · Electrical Eng. & Systems 2022-10-18 Damian Owerko , Fernando Gama , Alejandro Ribeiro

A $k$-defective clique of an undirected graph $G$ is a subset of its vertices that induces a nearly complete graph with a maximum of $k$ missing edges. The maximum $k$-defective clique problem, which asks for the largest $k$-defective…

Data Structures and Algorithms · Computer Science 2024-07-25 Chunyu Luo , Yi Zhou , Zhengren Wang , Mingyu Xiao