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Related papers: Routing Complexity of Faulty Networks

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We consider a class of random, weighted networks, obtained through a redefinition of patterns in an Hopfield-like model and, by performing percolation processes, we get information about topology and resilience properties of the networks…

Statistical Mechanics · Physics 2015-05-30 Elena Agliari , Claudia Cioli , Enore Guadagnini

We study the computational complexity of routing multiple objects through a network in such a way that only few collisions occur: Given a graph $G$ with two distinct terminal vertices and two positive integers $p$ and $k$, the question is…

Computational Complexity · Computer Science 2017-05-11 Till Fluschnik , Marco Morik , Manuel Sorge

Multilayer networks have been found to be prone to abrupt cascading failures under random and targeted attacks, but most of the targeting algorithms proposed so far have been mainly tested on uncorrelated systems. Here we show that the size…

Physics and Society · Physics 2020-07-23 Andrea Santoro , Vincenzo Nicosia

We investigate simplified models of computer data networks and examine how the introduction of additional random links influences the performance of these net works. In general, the impact of additional random links on the performance of…

adap-org · Physics 2023-12-18 Henryk Fuks , Anna T. Lawniczak

The functionality of nodes in a network is often described by the structural feature of belonging to the giant component. However, when dealing with problems like transport, a more appropriate functionality criterion is for a node to belong…

Physics and Society · Physics 2021-02-03 Bnaya Gross , Ivan Bonamassa , Shlomo Havlin

It was experimentally observed that the majority of real-world networks follow power law degree distribution. The aim of this paper is to study the algorithmic complexity of such "typical" networks. The contribution of this work is twofold.…

Data Structures and Algorithms · Computer Science 2015-07-10 Paweł Brach , Marek Cygan , Jakub Łącki , Piotr Sankowski

Network optimization has generally been focused on solving network flow problems, but recently there have been investigations into optimizing network characteristics. Optimizing network connectivity to maximize the number of nodes within a…

Physics and Society · Physics 2020-08-03 Jeremy Auerbach , Hyun Kim

Percolation is a fundamental concept that brought new understanding on the robustness properties of complex systems. Here we consider percolation on weakly interacting networks, that is, network layers coupled together by much less…

Physics and Society · Physics 2019-04-10 Giacomo Rapisardi , Alex Arenas , Guido Caldarelli , Giulio Cimini

Several interesting approaches have been reported in the literature on complex networks, random walks, and hierarchy of graphs. While many of these works perform random walks on stable, fixed networks, in the present work we address the…

Social and Information Networks · Computer Science 2024-03-12 Alexandre Benatti , Luciano da F. Costa

Neural networks are becoming increasingly prevalent in software, and it is therefore important to be able to verify their behavior. Because verifying the correctness of neural networks is extremely challenging, it is common to focus on the…

Machine Learning · Computer Science 2019-02-19 Ravi Mangal , Aditya V. Nori , Alessandro Orso

Entanglement routing in near-term quantum networks consists of choosing the optimal sequence of short-range entanglements to combine through swapping operations to establish end-to-end entanglement between two distant nodes. Similar to…

Emerging Technologies · Computer Science 2024-08-05 Amar Abane , Michael Cubeddu , Van Sy Mai , Abdella Battou

We investigate the searchability of complex systems in terms of their interconnectedness. Associating searchability with the number and size of branch points along the paths between the nodes, we find that scale-free networks are relatively…

Disordered Systems and Neural Networks · Physics 2007-05-23 M. Rosvall , A. Gronlund , P. Minnhagen , K. Sneppen

We explore the robustness of complex networks against physical damage. We focus on spatially embedded network models and datasets where links are physical objects or physically transfer some quantity, which can be disrupted at any point…

Statistical Mechanics · Physics 2024-12-13 Luka Blagojević , Ivan Bonamassa , Márton Pósfai

We present and study the Static-Routing-Resiliency problem, motivated by routing on the Internet: Given a graph $G$, a unique destination vertex $d$, and an integer constant $c>0$, does there exist a static and destination-based routing…

Networking and Internet Architecture · Computer Science 2016-07-28 Marco Chiesa , Andrei Gurtov , Aleksander Mądry , Slobodan Mitrović , Ilya Nikolaevkiy , Aurojit Panda , Michael Schapira , Scott Shenker

In this letter, we propose a new routing strategy to improve the transportation efficiency on complex networks. Instead of using the routing strategy for shortest path, we give a generalized routing algorithm to find the so-called {\it…

Disordered Systems and Neural Networks · Physics 2007-05-23 Gang Yan , Tao Zhou , Bo Hu , Zhong-Qian Fu , Bing-Hong Wang

Wormhole routing, the latest switching technique to be utilized by massively parallel computers, enjoys the distinct advantage of a low latency when compared to other switching techniques. This low latency is due to the nearly distance…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-08-31 Denvil Smith

Theoretical and empirical evidence indicates that the depth of neural networks is crucial for their success. However, training becomes more difficult as depth increases, and training of very deep networks remains an open problem. Here we…

Machine Learning · Computer Science 2015-11-24 Rupesh Kumar Srivastava , Klaus Greff , Jürgen Schmidhuber

We study percolation on networks, which is used as a model of the resilience of networked systems such as the Internet to attack or failure and as a simple model of the spread of disease over human contact networks. We reformulate…

Statistical Mechanics · Physics 2014-11-20 Brian Karrer , M. E. J. Newman , Lenka Zdeborová

Recent theoretical work has demonstrated that deep neural networks have superior performance over shallow networks, but their training is more difficult, e.g., they suffer from the vanishing gradient problem. This problem can be typically…

Machine Learning · Statistics 2021-11-03 Lu Lu , Yanhui Su , George Em Karniadakis

In the Minimum Clique Routing Problem on Cycles \textsc{MCRPC} we are given a cycle together with a set of demands (weighted origin-destination pairs) and the goal is to route all the pairs minimizing the maximum weighted clique of the…

Data Structures and Algorithms · Computer Science 2023-11-17 Mariana Escalante , Martín Matamala , Iván Rapaport , Paola Tolomei , Luis Miguel Torres