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The Laplacian matrix and its pseudo-inverse for a strongly connected directed graph is fundamental in computing many properties of a directed graph. Examples include random-walk centrality and betweenness measures, average hitting and…

Numerical Analysis · Mathematics 2020-09-16 Daniel Boley

The load-flow equations are the main tool to operate and plan electrical networks. For transmission or distribution networks these equations can be simplified into a linear system involving the graph Laplacian and the power input vector. We…

Classical Physics · Physics 2019-05-15 J. G. Caputo , A. Knippel , N. Retiere

We tackle the network topology inference problem by utilizing Laplacian constrained Gaussian graphical models, which recast the task as estimating a precision matrix in the form of a graph Laplacian. Recent research \cite{ying2020nonconvex}…

Machine Learning · Computer Science 2023-09-06 Jiaxi Ying , Xi Han , Rui Zhou , Xiwen Wang , Hing Cheung So

Accurate routing network status estimation is a key component in Software Defined Networking. However, existing deep-learning-based methods for modeling network routing are not able to extrapolate towards unseen feature distributions. Nor…

Networking and Internet Architecture · Computer Science 2024-04-29 Yifei Jin , Marios Daoutis , Sarunas Girdzijauskas , Aristides Gionis

We study the inverse problem of determining the conductivity matrix of an electrical network from the prescribed knowledge of the magnitude of the induced current along the edges coupled with the imposed voltage or injected current on the…

Analysis of PDEs · Mathematics 2018-10-16 Christina Knox , Amir Moradifam

We use queueing networks to present a new approach to solving Laplacian systems. This marks a significant departure from the existing techniques, mostly based on graph-theoretic constructions and sampling. Our distributed solver works for a…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-11 Iqra Altaf Gillani , Amitabha Bagchi

The computation of electrical flows is a crucial primitive for many recently proposed optimization algorithms on weighted networks. While typically implemented as a centralized subroutine, the ability to perform this task in a fully…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-01 Luca Becchetti , Vincenzo Bonifaci , Emanuele Natale

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

Urban intersections are prone to delays and inefficiencies due to static precedence rules and occlusions limiting the view on prioritized traffic. Existing approaches to improve traffic flow, widely known as automatic intersection…

Robotics · Computer Science 2022-07-27 Marvin Klimke , Benjamin Völz , Michael Buchholz

Oblivious routing is an attractive paradigm for large distributed systems in which centralized control and frequent reconfigurations are infeasible or undesired (e.g., costly). Over the last almost 20 years, much progress has been made in…

Networking and Internet Architecture · Computer Science 2018-12-27 Harald Räcke , Stefan Schmid

We investigate how the underlying graph of a network supports a flow between a source node and a destination node and propose to compute the expected number of nodes and links that contribute to transferring items in random graphs. Since…

Mathematical Physics · Physics 2026-03-04 Zhihao Qiu , Xinhan Liu , Rogier Noldus , Piet Van Mieghem

In this work we study the degree distribution, the maximum vertex and edge flow in non-uniform random Delaunay triangulations when geodesic routing is used. We also investigate the vertex and edge flow in Erd\"os-Renyi random graphs,…

Differential Geometry · Mathematics 2012-03-23 John D. Hobby , Gabriel H. Tucci

Flows over time are used to model many real-world logistic and routing problems. The networks underlying such problems -- streets, tracks, etc. -- are inherently undirected and directions are only imposed on them to reduce the danger of…

Data Structures and Algorithms · Computer Science 2014-10-03 Ashwin Arulselvan , Martin Groß , Martin Skutella

We revisit existing linear computation coding (LCC) algorithms, and introduce a new framework that measures the computational cost of computing multidimensional linear functions, not only in terms of the number of additions, but also with…

Information Theory · Computer Science 2024-01-17 Hans Rosenberger , Ali Bereyhi , Ralf R. Müller

The network reconfiguration problem seeks to find a rooted tree $T$ such that the energy of the (unique) feasible electrical flow over $T$ is minimized. The tree requirement on the support of the flow is motivated by operational constraints…

Data Structures and Algorithms · Computer Science 2023-08-24 Swati Gupta , Ali Khodabakhsh , Hassan Mortagy , Evdokia Nikolova

In this paper we derive an analytical expression for the mean load at each node of an arbitrary undirected graph for the uniform multicommodity flow problem under random walk routing. We show the mean load is linearly dependent on the nodal…

Disordered Systems and Neural Networks · Physics 2013-09-03 Onuttom Narayan , Iraj Saniee , Vladimir Marbukh

We present faster algorithms for approximate maximum flow in undirected graphs with good separator structures, such as bounded genus, minor free, and geometric graphs. Given such a graph with $n$ vertices, $m$ edges along with a recursive…

Data Structures and Algorithms · Computer Science 2012-10-19 Gary Miller , Richard Peng

The traffic assignment problem is one of the significant components of traffic flow analysis for which various solution approaches have been proposed. However, deploying these approaches for large-scale networks poses significant…

Machine Learning · Computer Science 2024-10-18 Tong Liu , Hadi Meidani

Graphical flows add further structure to normalizing flows by encoding non-trivial variable dependencies. Previous graphical flow models have focused primarily on a single flow direction: the normalizing direction for density estimation, or…

Machine Learning · Computer Science 2022-04-27 Jacobie Mouton , Steve Kroon

Emerging reconfigurable optical communication technologies allow to enhance datacenter topologies with demand-aware links optimized towards traffic patterns. This paper studies the algorithmic problem of jointly optimizing topology and…

Performance · Computer Science 2024-01-10 Wenkai Dai , Michael Dinitz , Klaus-Tycho Foerster , Long Luo , Stefan Schmid