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We propose and study a model of traffic in communication networks. The underlying network has a structure that is tunable between a scale-free growing network with preferential attachments and a random growing network. To model realistic…

Networking and Internet Architecture · Computer Science 2008-06-12 Zonghua Liua , Weichuan Ma , Huan Zhang , Yin Sun , P. M. Hui

We show that the connectivity distributions $P(k,t)$ of scale-free growing networks ($t$ is the network size) have the generic scale -- the cut-off at $k_{cut} \sim t^\beta$. The scaling exponent $\beta$ is related to the exponent $\gamma$…

Statistical Mechanics · Physics 2009-10-31 S. N. Dorogovtsev , J. F. F. Mendes , A. N. Samukhin

A prominent parameter in the context of network analysis, originally proposed by Watts and Strogatz (Collective dynamics of `small-world' networks, Nature 393 (1998) 440-442), is the clustering coefficient of a graph $G$. It is defined as…

Combinatorics · Mathematics 2016-11-21 Michael Gentner , Irene Heinrich , Simon Jäger , Dieter Rautenbach

We consider a class of simple, non-trivial models of evolving weighted scale-free networks. The network evolution in these models is determined by attachment of new vertices to ends of preferentially chosen weighted edges. Resulting…

Statistical Mechanics · Physics 2007-05-23 S. N. Dorogovtsev , J. F. F. Mendes

Small-world networks are the focus of recent interest because they appear to circumvent many of the limitations of either random networks or regular lattices as frameworks for the study of interaction networks of complex systems. Here, we…

Statistical Mechanics · Physics 2012-03-08 Luis A. Nunes Amaral , Antonio Scala , Marc Barthelemy , H. Eugene Stanley

In this letter, we propose a simple rule that generates scale-free networks with very large clustering coefficient and very small average distance. These networks are called {\bf Random Apollonian Networks}(RANs) as they can be considered…

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

Random graphs with power-law degrees can model scale-free networks as sparse topologies with strong degree heterogeneity. Mathematical analysis of such random graphs proved successful in explaining scale-free network properties such as…

Physics and Society · Physics 2019-05-24 Clara Stegehuis , Remco van der Hofstad , Johan S. H. van Leeuwaarden

A majority of studied models for scale-free networks have degree distributions with exponents greater than $2$. Real networks, however, can demonstrate essentially more heavy-tailed degree distributions. We explore two models of scale-free…

Physics and Society · Physics 2016-12-14 Gábor Timár , Sergey N. Dorogovtsev , José Fernando F. Mendes

Using a simple model with link removals as well as link additions, we show that an evolving network is scale free with a degree exponent in the range of (2, 4]. We then establish a relation between the network evolution and a set of…

Mathematical Physics · Physics 2007-05-23 Dinghua Shi , Liming Liu , Xiang Zhu , Huijie Zhou , Binbin Wang

The Internet, as well as many other networks, has a very complex connectivity recently modeled by the class of scale-free networks. This feature, which appears to be very efficient for a communications network, favors at the same time the…

Statistical Mechanics · Physics 2009-10-31 Romualdo Pastor-Satorras , Alessandro Vespignani

Many real-world networks have high clustering among vertices: vertices that share neighbors are often also directly connected to each other. A network's clustering can be a useful indicator of its connectedness and community structure.…

Social and Information Networks · Computer Science 2018-04-12 Jeff Alstott , Christine Klymko , Pamela B. Pyzza , Mary Radcliffe

Complex networks are characterized by several topological properties: degree distribution, clustering coefficient, average shortest path length, etc. Using a simple model to generate scale-free networks embedded on geographical space, we…

Disordered Systems and Neural Networks · Physics 2013-11-20 Satoru Morita

One of the main characteristics of real-world networks is their large clustering. Clustering is one aspect of a more general but much less studied structural organization of networks, i.e. edge multiplicity, defined as the number of…

Physics and Society · Physics 2012-01-31 Vinko Zlatic , Diego Garlaschelli , Guido Caldarelli

A central claim in modern network science is that real-world networks are typically "scale free," meaning that the fraction of nodes with degree $k$ follows a power law, decaying like $k^{-\alpha}$, often with $2 < \alpha < 3$. However,…

Physics and Society · Physics 2019-03-19 Anna D. Broido , Aaron Clauset

We develop a theoretical approach to percolation in random clustered networks. We find that, although clustering in scale-free networks can strongly affect some percolation properties, such as the size and the resilience of the giant…

Disordered Systems and Neural Networks · Physics 2009-11-11 M. Angeles Serrano , Marian Boguna

Despite their diverse origin, networks of large real-world systems reveal a number of common properties including small-world phenomena, scale-free degree distributions and modularity. Recently, network self-similarity as a natural outcome…

Adaptation and Self-Organizing Systems · Physics 2012-02-09 Neli Blagus , Lovro Šubelj , Marko Bajec

How does the shape of a network change as its size increases? Although random graph models provide some expectations for such "scaling behaviors" in the structure of networks, relatively little is known about how empirical network structure…

Social and Information Networks · Computer Science 2026-03-24 Upasana Dutta , Alexander Ray , Aaron Clauset

Real world complex networks are scale free and possess meso-scale properties like core-periphery and community structure. We study evolution of the core over time in real world networks. This paper proposes evolving models for both…

Social and Information Networks · Computer Science 2015-12-01 Akrati Saxena , S. R. S. Iyengar

We propose a simple rule that generates scale-free networks with very large clustering coefficient and very small average distance. These networks are called simplex triangulation networks(STNs) as they can be considered as a kind of…

Statistical Mechanics · Physics 2007-05-23 Zhi-Ming Gu , Tao Zhou , Bing-Hong Wang , Gang Yan , Chen-Ping Zhu , Zhong-Qian Fu

We propose a simple algorithm which produces a new category of networks, high dimensional random Apollonian networks, with small-world and scale-free characteristics. We derive analytical expressions for their degree distributions and…

Other Condensed Matter · Physics 2009-11-11 Zhongzhi Zhang , Lili Rong , Francesc Comellas
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