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Related papers: Network connectivity analysis via shortest paths

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The connectivity structure of graphs is typically related to the attributes of the nodes. In social networks for example, the probability of a friendship between two people depends on their attributes, such as their age, address, and…

Social and Information Networks · Computer Science 2020-02-06 Junning Deng , Bo Kang , Jefrey Lijffijt , Tijl De Bie

Network flow is a powerful mathematical framework to systematically explore the relationship between structure and function in biological, social, and technological networks. We introduce a new pipelining model of flow through networks…

Neural and Evolutionary Computing · Computer Science 2019-11-04 Lavanya Marla , Lav R. Varshney , Devavrat Shah , Nirmal A. Prakash , Michael E. Gale

For a graph $G$ and $a,b\in V(G)$, the shortest path reconfiguration graph of $G$ with respect to $a$ and $b$ is denoted by $S(G,a,b)$. The vertex set of $S(G,a,b)$ is the set of all shortest paths between $a$ and $b$ in $G$. Two vertices…

Combinatorics · Mathematics 2017-05-29 John Asplund , Kossi Edoh , Ruth Haas , Yulia Hristova , Beth Novick , Brett Werner

This paper deals with dynamical networks for which the relations between node signals are described by proper transfer functions and external signals can influence each of the node signals. In particular, we are interested in…

Optimization and Control · Mathematics 2018-07-24 Henk J. van Waarde , Pietro Tesi , M. Kanat Camlibel

Many topological and dynamical properties of complex networks are defined by assuming that most of the transport on the network flows along the shortest paths. However, there are different scenarios in which non-shortest paths are used to…

Physics and Society · Physics 2008-12-16 Ernesto Estrada , Naomichi Hatano

Graphs are fundamental objects that find widespread applications across computer science and beyond. Graph Theory has yielded deep insights about structural properties of various families of graphs, which are leveraged in the design and…

Data Structures and Algorithms · Computer Science 2023-08-30 Rachit Nimavat

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

The \emph{$k$-restricted edge-connectivity} of a graph $G$, denoted by $\lambda_k(G)$, is defined as the minimum size of an edge set whose removal leaves exactly two connected components each containing at least $k$ vertices. This graph…

Data Structures and Algorithms · Computer Science 2016-09-20 Luis Pedro Montejano , Ignasi Sau

Given a graph $G(V, E)$ and a positive integer $k$ ($k \geq 1$), a simple path on $k$ vertices is a sequence of $k$ vertices in which no vertex appears more than once and each consecutive pair of vertices in the sequence are connected by an…

Data Structures and Algorithms · Computer Science 2023-04-18 Thai Bui

One model of message delivery in a computer network is based on labelling each edge by a subset of a (reasonably small) universal set, and then encoding a path as the union of the labels of its edges. Earlier work suggested using random…

Combinatorics · Mathematics 2018-06-26 Gokce Caylak Kayaturan , Alexei Vernitski

The degree centrality of a node, defined as the number of nodes adjacent to it, is often used as a measure of importance of a node to the structure of a network. This metric can be extended to paths in a network, where the degree centrality…

Data Structures and Algorithms · Computer Science 2025-12-19 Johnson Phosavanh , Dmytro Matsypura

The complexity of highly interconnected systems is rooted in the interwoven architecture defined by its connectivity structure. In this paper, we develop matrix energy of the underlying connectivity structure as a measure of topological…

Physics and Society · Physics 2016-08-31 Kaushik Sinha , Olivier L. de Weck

Multivariate graphs are prolific across many fields, including transportation and neuroscience. A key task in graph analysis is the exploration of connectivity, to, for example, analyze how signals flow through neurons, or to explore how…

Social networks are of interest to researchers in part because they are thought to mediate the flow of information in communities and organizations. Here we study the temporal dynamics of communication using on-line data, including e-mail…

Physics and Society · Physics 2008-06-20 Gueorgi Kossinets , Jon Kleinberg , Duncan Watts

Various hypotheses exist about the paths used for communication between the nodes of complex networks. Most studies simply suppose that communication goes via shortest paths, while others have more explicit assumptions about how routing…

Networks are useful for describing systems of interacting objects, where the nodes represent the objects and the edges represent the interactions between them. The applications include chemical and metabolic systems, food webs as well as…

Computational Physics · Physics 2009-10-20 Baruch Barzel , Ofer Biham

We introduce the problem of finding a spanning tree along with a partition of the tree edges into fewest number of feasible sets, where constraints on the edges define feasibility. The motivation comes from wireless networking, where we…

Networking and Internet Architecture · Computer Science 2018-03-14 Magnus M. Halldorsson , Guy Kortsarz , Pradipta Mitra , Tigran Tonoyan

Internet is a complex network composed by several networks: the Autonomous Systems, each one designed to transport information efficiently. Routing protocols aim to find paths between nodes whenever it is possible (i.e., the network is not…

Discrete Mathematics · Computer Science 2012-02-21 José Ignacio Alvarez-Hamelin , Beiró Mariano Gastón , Jorge Rodolfo Busch

The method is based on the preliminary transformation of the traditionally used matrices or adjacency lists in the graph theory into refined projections free from redundant information, and their subsequent use in constructing shortest…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-25 V. A. Melent'ev

Seeking effective neural networks is a critical and practical field in deep learning. Besides designing the depth, type of convolution, normalization, and nonlinearities, the topological connectivity of neural networks is also important.…

Computer Vision and Pattern Recognition · Computer Science 2020-08-20 Kun Yuan , Quanquan Li , Jing Shao , Junjie Yan