Scale-free Network with Variable Scaling Exponent

2010 ◽  
Author(s):  
Bing Ye ◽  
Zhenting Hou ◽  
Xiang Kong
Keyword(s):  
Scaling Exponent ◽  
Scale Free Network ◽  
Scale Free ◽  
Free Network

A Weighted Scale-Free Network with Triad Formation

2011 ◽  
Vol 225-226 ◽  
pp. 442-445
Author(s):  
Shu Liang Li ◽  
Dan Wang ◽  
Le Zhang
Keyword(s):  
Real Life ◽  
Evolutionary Model ◽  
Scaling Exponent ◽  
Scale Free Network ◽  
Average Strength ◽  
Weighted Network ◽  
Scale Free ◽  
Free Network ◽  
Weighted Model ◽  
Power Law Distributions

We propose an evolutionary model for weighted network according to characteristics of real-life network, and the weighted model integrates the triad formation and the preferential mechanism. The two mechanisms provide a wide variety of scale-free behaviors depending on the parameter that govern the new nodes and new links growth. The model gives power-law distributions of degree, weight, and strength. In particular, the average strength displays scale-free property , , as confirmed in many real networks. While in BBV weighted model, the scaling exponent . This implies that the strength of nodes grows faster than their degree. This denotes a strong correlation between the weight and the topological properties in the model, which can be considered as a meaningful development of weighted network model.

Research on new evolution model of scale-free network

2009 ◽  
Vol 29 (5) ◽  
pp. 1230-1232
Author(s):  
Hao RAO ◽  
Chun YANG ◽  
Shao-hua TAO
Keyword(s):  
Evolution Model ◽  
Scale Free Network ◽  
Scale Free ◽  
Free Network

scholarly journals Analysis on Invulnerability of Wireless Sensor Network towards Cascading Failures Based on Coupled Map Lattice

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Xiuwen Fu ◽  
Yongsheng Yang ◽  
Haiqing Yao
Keyword(s):  
Random Network ◽  
Small World ◽  
Coupled Map Lattice ◽  
Wireless Sensor ◽  
Cascading Failures ◽  
Scale Free Network ◽  
Scale Free ◽  
Network Topologies ◽  
Free Network ◽  
Entire Network

Previous research of wireless sensor networks (WSNs) invulnerability mainly focuses on the static topology, while ignoring the cascading process of the network caused by the dynamic changes of load. Therefore, given the realistic features of WSNs, in this paper we research the invulnerability of WSNs with respect to cascading failures based on the coupled map lattice (CML). The invulnerability and the cascading process of four types of network topologies (i.e., random network, small-world network, homogenous scale-free network, and heterogeneous scale-free network) under various attack schemes (i.e., random attack, max-degree attack, and max-status attack) are investigated, respectively. The simulation results demonstrate that the rise of interference R and coupling coefficient ε will increase the risks of cascading failures. Cascading threshold values Rc and εc exist, where cascading failures will spread to the entire network when R>Rc or ε>εc. When facing a random attack or max-status attack, the network with higher heterogeneity tends to have a stronger invulnerability towards cascading failures. Conversely, when facing a max-degree attack, the network with higher uniformity tends to have a better performance. Besides that, we have also proved that the spreading speed of cascading failures is inversely proportional to the average path length of the network and the increase of average degree k can improve the network invulnerability.

The Barabási and Albert scale-free network model

2018 ◽  
Vol 35 (1) ◽  
pp. 123-132 ◽  
Author(s):  
Lei Zhu ◽  
Lei Wang ◽  
Xiang Zheng ◽  
Yuzhang Xu
Keyword(s):  
Network Model ◽  
Scale Free Network ◽  
Scale Free ◽  
Free Network
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