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Rank-based deactivation model for aging networks
Wang Xuewen 1,Yang Guohong 2 *, Li Xiao-Lin 3, Xun Xin-Jian 3
1.Department of Physics, Shanghai University, ShangHai 200444
2.Department of Physics, Shanghai University, Shanghai 200444, China
3. Department of Mathematics, Shanghai University, Shanghai 200444, China
*Correspondence author
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Funding: 高等学校博士学科点专项科研基金资助课题(No.20093108110004)
Opened online:28 December 2012
Accepted by: none
Citation: Wang Xuewen,Yang Guohong, Li Xiao-Lin.Rank-based deactivation model for aging networks[OL]. [28 December 2012] http://en.paper.edu.cn/en_releasepaper/content/4508244
 
 
Reviews: We study aging networks which couple addition of new nodes anddeactivation of old ones. During network evolution, each nodeexperiences two stages: active and inactive. The transition from theactive state to the inactive one is based on the rank of the node.For simplicity, we adopt age as a criterion of ranking and proposetwo deactivation models that generalize previous research. In modelA, the older node possesses the higher rank, whereas for model B,the younger node takes the higher rank. We make comparable study ofthe two models through the node degree distribution.
Keywords:Complex Networks; Deactivation; Rank; Exponential cut-off
 
 
 

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