Abstract
In spite of the extensive previous efforts on traffic dynamics and epidemic spreading in complex networks, the problem of traffic-driven epidemic spreading on correlated networks has not been addressed. Interestingly, we find that the epidemic threshold, a fundamental quantity underlying the spreading dynamics, exhibits a nonmonotonic behavior in that it can be minimized for some critical value of the assortativity coefficient, a parameter characterizing the network correlation. To understand this phenomenon, we use the degree-based mean-field theory to calculate the traffic-driven epidemic threshold for correlated networks. The theory predicts that the threshold is inversely proportional to the packet-generation rate and the largest eigenvalue of the betweenness matrix. We obtain consistency between theory and numerics. Our results may provide insights into the important problem of controlling and/or harnessing real-world epidemic spreading dynamics driven by traffic flows.
Original language | English |
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Article number | 062817 |
Number of pages | 6 |
Journal | Physical Review. E, Statistical, Nonlinear and Soft Matter Physics |
Volume | 91 |
Issue number | 6 |
DOIs | |
Publication status | Published - 29 Jun 2015 |
Bibliographical note
ACKNOWLEDGMENTSThis work was supported by the National Science Foundation of China (Grants No. 61403083, No. 91324002, and No. 71301028) and the Natural Science Foundation of Fujian Province (Grant No. 2013J05007). Y.C.L. was supported by the Army Research Office (ARO) under Grant No. W911NF14-1-0504.
Keywords
- Traffic driven epidemic spreading
- correlated networks
- meanfield theory
- traffic flows