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This work considers the robustness of uncertain consensus networks. The first set of results studies the stability properties of consensus networks with negative edge weights. We show that if either the negative weight edges form a cut in…

Optimization and Control · Mathematics 2015-03-03 Daniel Zelazo , Mathias Bürger

One of the most important and well-studied settings for network design is edge-connectivity requirements. This encompasses uniform demands such as the Minimum $k$-Edge-Connected Spanning Subgraph problem ($k$-ECSS), as well as nonuniform…

Data Structures and Algorithms · Computer Science 2022-06-27 Michael Dinitz , Ama Koranteng , Guy Kortsarz

Let $G$ be a graph of order $n$ and let $u,v$ be vertices of $G$. Let $\kappa_G(u,v)$ denote the maximum number of internally disjoint $u$-$v$ paths in $G$. Then the average connectivity $\overline{\kappa}(G)$ of $G$, is defined as $…

Combinatorics · Mathematics 2021-07-23 Lucas Mol , Ortrud R. Oellermann , Vibhav Oswal

A k-connected graph such that deleting any edge / deleting any vertex / contracting any edge results in a graph which is not k-connected is called minimally / critically / contraction-critically k-connected. These three classes play a…

Combinatorics · Mathematics 2011-01-13 Matthias Kriesell

There has been recent growing interest in graph theoretical properties known as r- and (r,s)-robustness. These properties serve as sufficient conditions guaranteeing the success of certain consensus algorithms in networks with misbehaving…

Systems and Control · Computer Science 2017-10-06 James Usevitch , Dimitra Panagou

Security is an important issue in wireless sensor networks (WSNs), which are often deployed in hostile environments. The q-composite key predistribution scheme has been recognized as a suitable approach to secure WSNs. Although the…

Networking and Internet Architecture · Computer Science 2019-11-21 Jun Zhao

In this paper, we investigate the exact asymptotic behavior of the connectivity probability in the Erdos-Renyi graph G(n,p), under different asymptotic assumptions on the edge probability p=p(n). We propose a novel approach based on the…

Probability · Mathematics 2025-04-14 B. Chinyaev , A. Shklyaev

Let $G=G_{n,k}$ denote the graph formed by placing points in a square of area $n$ according to a Poisson process of density 1 and joining each pair of points which are both $k$ nearest neighbours of each other. Then $G_{n,k}$ can be used as…

Combinatorics · Mathematics 2014-06-04 Neville Ball

We formalize the problem of detecting a community in a network into testing whether in a given (random) graph there is a subgraph that is unusually dense. We observe an undirected and unweighted graph on N nodes. Under the null hypothesis,…

Statistics Theory · Mathematics 2013-03-01 Ery Arias-Castro , Nicolas Verzelen

We introduce a measure of {\em greedy connectivity} for geographical networks (graphs embedded in space) and where the search for connecting paths relies only on local information, such as a node's location and that of its neighbors.…

Statistical Mechanics · Physics 2015-05-18 Jie Sun , Daniel ben-Avraham

Predicting edges in networks is a key problem in social network analysis and involves reasoning about the relationships between nodes based on the structural properties of a network. In particular, link prediction can be used to analyse how…

Social and Information Networks · Computer Science 2020-01-01 Mateusz Tarkowski , Tomasz Michalak , Michael Wooldridge

We consider the Eschenauer-Gligor key predistribution scheme under the condition of partial visibility with i.i.d. on-off links between pairs of nodes. This situation is modeled as the intersection of two random graphs, namely a random key…

Probability · Mathematics 2015-10-13 Armand M. Makowski , Osman Yağan

We employ the mathematical programming approach in conjunction with the graph theory to study the structure of correspondent banking networks. Optimizing the network requires decisions to be made to onboard, terminate or restrict the bank…

Machine Learning · Computer Science 2019-12-09 Nima Safaei , Ivan A. Sergienko

Two models are introduced to investigate graph matching in the presence of corrupt nodes. The weak model, inspired by biological networks, allows one or both networks to have a positive fraction of molecular entities interact randomly with…

Statistics Theory · Mathematics 2023-11-02 Taha Ameen , Bruce Hajek

Nodes are randomly distributed within an annulus (and then a shell) to form a point pattern of communication terminals which are linked stochastically according to the Rayleigh fading of radio-frequency data signals. We then present…

Combinatorics · Mathematics 2017-06-15 Alexander P. Kartun-Giles , Orestis Georgiou , Carl P. Dettmann

Graph connectivity is a fundamental combinatorial optimization problem that arises in many practical applications, where usually a spanning subgraph of a network is used for its operation. However, in the real world, links may fail…

Data Structures and Algorithms · Computer Science 2022-09-13 Dimitris Fotakis , Evangelia Gergatsouli , Charilaos Pipis , Miltiadis Stouras , Christos Tzamos

The random graph of Erdos and Renyi is one of the oldest and best studied models of a network, and possesses the considerable advantage of being exactly solvable for many of its average properties. However, as a model of real-world networks…

Statistical Mechanics · Physics 2007-05-23 M. E. J. Newman

We show that if a graph is k-edge-connected, and we adjoin to it another graph satisfying a "contracted diameter less or equal to 2" condition, with minimal degree greater or equal to k, and some natural hypothesis on the edges connecting…

General Mathematics · Mathematics 2008-12-18 José Ignacio Alvarez-Hamelin , Jorge Rodolfo Busch

Given an undirected graph, the resistance distance between two nodes is the resistance one would measure between these two nodes in an electrical network if edges were resistors. Summing these distances over all pairs of nodes yields the…

Information Theory · Computer Science 2015-10-01 Nicolas Boumal , Xiuyuan Cheng

The simplest null models for networks, used to distinguish significant features of a particular network from {\it a priori} expected features, are random ensembles with the degree sequence fixed by the specific network of interest. These…

Statistical Mechanics · Physics 2009-11-11 Jacob G. Foster , David V. Foster , Peter Grassberger , Maya Paczuski
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