WEIGHT-DEPENDENT WALKS AND AVERAGE SHORTEST WEIGHTED PATH ON THE WEIGHTED ITERATED FRIENDSHIP GRAPHS
Yan Liu,
Meifeng Dai and
Yuanyuan Guo
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Yan Liu: School of Mathematical Sciences, Jiangsu University, Zhenjiang 212013, P. R. China
Meifeng Dai: School of Mathematical Sciences, Jiangsu University, Zhenjiang 212013, P. R. China
Yuanyuan Guo: School of Mathematical Sciences, Jiangsu University, Zhenjiang 212013, P. R. China
FRACTALS (fractals), 2022, vol. 30, issue 06, 1-14
Abstract:
In this paper, we present the weighted iterated friendship graphs and study the trapping problem on the weighted iterated friendship graphs. It can be found that for 0 < r < 1 and r = 1, the relationship between the average trapping time (ATT) and network size is sublinear and linear, respectively. By controlling the parameters of the weighted iterated friendship graphs, the models are changed to the self-similar weighted networks. The average shortest weighted path (ASWP) in the self-similar weighted friendship graphs is studied. The results show that when 0 < r < 1, the ASWP is bounded, and when r = 1, the ASWP is linearly related to the order of the networks.
Keywords: Weighted Iterated Friendship Graphs; Average Trapping Time; Weight-Dependent Walks; Average Shortest Weighted Path (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0218348X22501092
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