Mean first return time for random walks on weighted networks

Xing-Li Jing, Xiang Ling, Jiancheng Long, Qing Shi and Mao-Bin Hu ()
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Xing-Li Jing: School of Transportation Engineering, Hefei University of Technology, Hefei 230009, P. R. China
Xiang Ling: School of Transportation Engineering, Hefei University of Technology, Hefei 230009, P. R. China
Jiancheng Long: School of Transportation Engineering, Hefei University of Technology, Hefei 230009, P. R. China
Qing Shi: School of Transportation Engineering, Hefei University of Technology, Hefei 230009, P. R. China
Mao-Bin Hu: School of Engineering Science, University of Science and Technology of China, Hefei 230026, P. R. China

International Journal of Modern Physics C (IJMPC), 2015, vol. 26, issue 06, 1-9

Abstract: Random walks on complex networks are of great importance to understand various types of phenomena in real world. In this paper, two types of biased random walks on nonassortative weighted networks are studied: edge-weight-based random walks and node-strength-based random walks, both of which are extended from the normal random walk model. Exact expressions for stationary distribution and mean first return time (MFRT) are derived and examined by simulation. The results will be helpful for understanding the influences of weights on the behavior of random walks.

Keywords: Mean first return time; random walks; weighted networks; 89.75.Hc; 05.40.Fb; 89.75.Da (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1142/S0129183115500680

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