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Related papers: Scale-free networks embedded in fractal space

200 papers

A large number of complex networks, both natural and artificial, share the presence of highly heterogeneous, scale-free degree distributions. A few mechanisms for the emergence of such patterns have been suggested, optimization not being…

Statistical Mechanics · Physics 2009-11-07 S. Valverde , R. Ferrer i Cancho , R. V. Sole

Real-life networks often encounter vertex dysfunctions, which are usually followed by recoveries after appropriate maintenances. In this paper we present our research on a model of scale-free networks whose vertices are regularly removed…

Physics and Society · Physics 2013-10-08 Linjun Li , Xiangwen Wang

We analyze the degree distribution's cut-off in finite size scale-free networks. We show that the cut-off behavior with the number of vertices $N$ is ruled by the topological constraints induced by the connectivity structure of the network.…

Disordered Systems and Neural Networks · Physics 2009-11-10 Marian Boguna , Romualdo Pastor-Satorras , Alessandro Vespignani

Since a spatial distribution of communication requests is inhomogeneous and related to a population, in constructing a network, it is crucial for delivering packets on short paths through the links between proximity nodes and for…

Physics and Society · Physics 2012-07-31 Yukio Hayashi

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

Real networks can be classified into two categories: fractal networks and non-fractal networks. Here we introduce a unifying model for the two types of networks. Our model network is governed by a parameter $q$. We obtain the topological…

Other Condensed Matter · Physics 2008-08-07 Zhongzhi Zhang , Shuigeng Zhou , Lichao Chen , Jihong Guan

A random sequential box-covering algorithm recently introduced to measure the fractal dimension in scale-free networks is investigated. The algorithm contains Monte Carlo sequential steps of choosing the position of the center of each box,…

Statistical Mechanics · Physics 2008-04-29 J. S. Kim , K. -I. Goh , B. Kahng , D. Kim

Wireless mesh networks (WMNs) depend on the spatial distribution of nodes, which directly influences connectivity, routing efficiency, and overall network performance. Conventional models typically assume uniform or random node placement,…

Networking and Internet Architecture · Computer Science 2025-12-01 Marat Zaidyn , Sayat Akhtanov , Dana Turlykozhayeva , Symbat Temesheva , Almat Akhmetali , Alisher Skabylov , Nurzhan Ussipov

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

Different weighted scale-free networks show weights-topology correlations indicated by the non linear scaling of the node strength with node connectivity. In this paper we show that networks with and without weight-topology correlations can…

Disordered Systems and Neural Networks · Physics 2009-11-10 Ginestra Bianconi

This article addresses the degree distribution of subnetworks, namely the number of links between the nodes in each subnetwork and the remainder of the structure (cond-mat/0408076). The transformation from a subnetwork-partitioned model to…

Disordered Systems and Neural Networks · Physics 2007-05-23 Luciano da Fontoura Costa

We investigate a network model based on an infinite regular square lattice embedded in the Euclidean plane where the node connection probability is given by the geometrical distance of nodes. We show that the degree distribution in the…

Physics and Society · Physics 2008-06-23 Matus Medo , Jan Smrek

A complete understanding of real networks requires us to understand the consequences of the uneven interaction strengths between a system's components. Here we use the minimum spanning tree (MST) to explore the effect of weight assignment…

Disordered Systems and Neural Networks · Physics 2007-05-23 P. J. Macdonald , E. Almaas , A. -L. Barabasi

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

Networks in nature are often formed within a spatial domain in a dynamical manner, gaining links and nodes as they develop over time. We propose a class of spatially-based growing network models and investigate the relationship between the…

Physics and Society · Physics 2013-12-30 Ari Zitin , Alex Gorowora , Shane Squires , Mark Herrera , Thomas M. Antonsen , Michelle Girvan , Edward Ott

We study the effects of spatial constraints on the structural properties of networks embedded in one or two dimensional space. When nodes are embedded in space, they have a well defined Euclidean distance $r$ between any pair. We assume…

Physics and Society · Physics 2009-11-13 Kosmas Kosmidis , Shlomo Havlin , Armin Bunde

We study scale free simple graphs with an exponent of the degree distribution $\gamma$ less than two. Generically one expects such extremely skewed networks -- which occur very frequently in systems of virtually or logically connected units…

Statistical Mechanics · Physics 2007-05-23 Hamed Seyed-allaei , Ginestra Bianconi , Matteo Marsili

We study the percolation phase transition in hierarchical scale-free nets. Depending on the method of construction, the nets can be fractal or small-world (the diameter grows either algebraically or logarithmically with the net size),…

Statistical Mechanics · Physics 2009-11-13 Hernán D. Rozenfeld , Daniel ben-Avraham

We show that fractality in complex networks arises from the geometric self-similarity of their built-in hierarchical community-like structure, which is mathematically described by the scale-invariant equation for the masses of the boxes…

We propose a general geometric growth model for pseudofractal scale-free web, which is controlled by two tunable parameters. We derive exactly the main characteristics of the networks: degree distribution, second moment of degree…

Statistical Mechanics · Physics 2007-05-23 Zhongzhi Zhang , Lili Rong , Shuigeng Zhou