Weighted gradient networks on complex networks

被引：0
作者：
机构：
[1] Institute of Information Science, Beijing Jiaotong University
来源：
Liang, M. (mgliang58@gmail.com) | 1879年 / Binary Information Press, Flat F 8th Floor, Block 3, Tanner Garden, 18 Tanner Road, Hong Kong卷 / 10期
关键词：
Complex network; Computer network; Gradient network; Jamming; Weight;
D O I：
10.12733/jics20101722
中图分类号：
学科分类号：
摘要：
This paper reports the finding of a weighted gradient network model on the unweighted substrate networks, where the edge weight depends on the degree of the node it connects and a tunable parameter α. With the new definition of the jamming coefficient, the results of numerical simulations show that in both Barabási-Albert (BA) scale-free networks and Erdös-Rényi (ER) random networks, the jamming coefficient becomes larger with the increase of average degree <k> for the same α. Furthermore, there exists a critical value of αc in two networks with the same average degree. For α < αc, the ER random network has a higher level of congestion than BA scale-free network, while α > αc the opposite occurs. © 2013 by Binary Information Press.
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页码：1879 / 1886
页数：7
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