Weighted Scaling in Non-growth Random Networks  

Weighted Scaling in Non-growth Random Networks

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作  者:陈光 杨旭华 徐新黎 

机构地区:[1]College of Computer Science and Technology,Zhejiang University of Technology

出  处:《Communications in Theoretical Physics》2012年第9期456-462,共7页理论物理通讯(英文版)

基  金:Supported by the National Natural Science Foundation of China under Grant No.60874080;the Commonweal Application Technique Research Project of Zhejiang Province under Grant No.2012C2316;the Open Project of State Key Lab of Industrial Control Technology of Zhejiang University under Grant No.ICT1107

摘  要:We propose a weighted model to explain the self-organizing formation of scale-free phenomenon in nongrowth random networks. In this model, we use multiple-edges to represent the connections between vertices and define the weight of a multiple-edge as the total weights of all single-edges within it and the strength of a vertex as the sum of weights for those multiple-edges attached to it. The network evolves according to a vertex strength preferential selection mechanism. During the evolution process, the network always holds its totM number of vertices and its total number of single-edges constantly. We show analytically and numerically that a network will form steady scale-free distributions with our model. The results show that a weighted non-growth random network can evolve into scMe-free state. It is interesting that the network also obtains the character of an exponential edge weight distribution. Namely, coexistence of scale-free distribution and exponential distribution emerges.

关 键 词:weighted network random network non-growth scale-free distribution 

分 类 号:O157.5[理学—数学]

 

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