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We investigate the growth of connectivity in a network. In our model, starting with a set of disjoint nodes, links are added sequentially. Each link connects two nodes, and the connection rate governing this random process is proportional…

统计力学 · 物理学 2012-02-16 E. Ben-Naim , P. L. Krapivsky

Based on the empirical analysis of the dependency network in 18 Java projects, we develop a novel model of network growth which considers both: an attachment mechanism and the addition of new nodes with a heterogeneous distribution of their…

物理与社会 · 物理学 2015-05-19 Claudio J. Tessone , Markus M. Geipel , F. Schweitzer

We propose a new preferential attachment-based network growth model in order to explain two properties of growing networks: (1) the power-law growth of node degrees and (2) the decay of node relevance. In preferential attachment models, the…

物理与社会 · 物理学 2018-04-10 Jun Sun , Steffen Staab , Fariba Karimi

Many complex networks from the World-Wide-Web to biological networks are growing taking into account the heterogeneous features of the nodes. The feature of a node might be a discrete quantity such as a classification of a URL document as…

物理与社会 · 物理学 2013-05-30 Luca Ferretti , Michele Cortelezzi , Bin Yang , Giacomo Marmorini , Ginestra Bianconi

A network growth mechanism based on a two-step preferential rule is investigated as a model of network growth in which no global knowledge of the network is required. In the first filtering step a subset of fixed size $m$ of existing nodes…

无序系统与神经网络 · 物理学 2009-11-10 Hrvoje Stefancic , Vinko Zlatic

We introduce a network growth model based on complete redirection: a new node randomly selects an existing target node, but attaches to a random neighbor of this target. For undirected networks, this simple growth rule generates unusual,…

物理与社会 · 物理学 2017-07-27 P. L. Krapivsky , S. Redner

Many growing networks possess accelerating statistics where the number of links added with each new node is an increasing function of network size so the total number of links increases faster than linearly with network size. In particular,…

分子网络 · 定量生物学 2017-12-22 M. J. Gagen , J. S. Mattick

We introduce a growing network model---the copying model---in which a new node attaches to a randomly selected target node and, in addition, independently to each of the neighbors of the target with copying probability $p$. When…

统计力学 · 物理学 2016-12-14 U. Bhat , P. L. Krapivsky , R. Lambiotte , S. Redner

A network as a substrate for dynamic processes may have its own dynamics. We propose a model for networks which evolve together with diffusing particles through a coupled dynamics, and investigate emerging structural property. The model…

统计力学 · 物理学 2009-11-10 Sang-Woo Kim , Jae Dong Noh

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…

数学物理 · 物理学 2007-05-23 Dinghua Shi , Liming Liu , Xiang Zhu , Huijie Zhou , Binbin Wang

The parallel computational complexity or depth of growing network models is investigated. The networks considered are generated by preferential attachment rules where the probability of attaching a new node to an existing node is given by a…

统计力学 · 物理学 2009-11-10 Benjamin Machta , Jonthan Machta

We derive asymptotic properties for a stochastic dynamic network model in a stochastic dynamic population. In the model, nodes give birth to new nodes until they die, each node being equipped with a social index given at birth. During the…

概率论 · 数学 2019-07-10 Tom Britton , Mathias Lindholm , Tatyana Turova

In this paper, we propose an evolving network model growing fast in units of module, based on the analysis of the evolution characteristics in real complex networks. Each module is a small-world network containing several interconnected…

物理与社会 · 物理学 2011-10-11 Zou Zhi-Yun , Liu Peng , Lei Li , Gao Jian-Zhi

We introduce a new class of networks that grow by enhanced redirection. Nodes are introduced sequentially, and each either attaches to a randomly chosen target node with probability 1-r or to the ancestor of the target with probability r,…

统计力学 · 物理学 2013-11-14 Alan Gabel , P. L. Krapivsky , S. Redner

In this article, we propose a growing network model based on an optimal policy involving both topological and geographical measures. In this model, at each time step, a new node, having randomly assigned coordinates in a $1 \times 1$…

物理与社会 · 物理学 2007-05-23 Yan-Bo Xie , Tao Zhou , Wen-Jie Bai , Guanrong Chen , Wei-Ke Xiao , Bing-Hong Wang

We investigate a model of evolving random network, introduced by us previously {[}{\it Phys. Rev. Lett.} {\bf 83}, 5587 (1999){]} . The model is a generalization of the Bak-Sneppen model of biological evolution, with the modification that…

统计力学 · 物理学 2009-10-31 Frantisek Slanina , Miroslav Kotrla

Analytical results are presented for the structure of networks that evolve via a preferential-attachment-random-deletion (PARD) model in the regime of overall network growth and in the regime of overall contraction. The phase transition…

统计力学 · 物理学 2025-01-13 Barak Budnick , Ofer Biham , Eytan Katzav

Network models with preferential attachment, where new nodes are injected into the network and form links with existing nodes proportional to their current connectivity, have been well studied for some time. Extensions have been introduced…

物理与社会 · 物理学 2013-06-26 James P. Bagrow , Dirk Brockmann

Network growth as described by the Duplication-Divergence model proposes a simple general idea for the evolution dynamics of natural networks. In particular it is an alternative to the well known Barab\'asi-Albert model when applied to…

Individual nodes in evolving real-world networks typically experience growth and decay --- that is, the popularity and influence of individuals peaks and then fades. In this paper, we study this phenomenon via an intrinsic nodal fitness…

物理与社会 · 物理学 2015-05-20 Xin-Jian Xu , Xiao-Long Peng , Michael Small , Xin-Chu Fu