Traffic-driven epidemic outbreak on complex networks: How long does it take?
Author(s) -
Han-Xin Yang,
Wen-Xu Wang,
Ying-Cheng Lai
Publication year - 2012
Publication title -
chaos an interdisciplinary journal of nonlinear science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.971
H-Index - 113
eISSN - 1089-7682
pISSN - 1054-1500
DOI - 10.1063/1.4772967
Subject(s) - betweenness centrality , complex network , computer science , rendering (computer graphics) , network packet , epidemic model , statistical physics , scale free network , mathematics , statistics , computer network , artificial intelligence , centrality , physics , population , world wide web , demography , sociology
Recent studies have suggested the necessity to incorporate traffic dynamics into the process of epidemic spreading on complex networks, as the former provides support for the latter in many real-world situations. While there are results on the asymptotic scope of the spreading dynamics, the issue of how fast an epidemic outbreak can occur remains outstanding. We observe numerically that the density of the infected nodes exhibits an exponential increase with time initially, rendering definable a characteristic time for the outbreak. We then derive a formula for scale-free networks, which relates this time to parameters characterizing the traffic dynamics and the network structure such as packet-generation rate and betweenness distribution. The validity of the formula is tested numerically. Our study indicates that increasing the average degree and/or inducing traffic congestion can slow down the spreading process significantly.
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