Name
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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1103/PhysRevE.91.062817 | PHYSICAL REVIEW E |
Field | DocType | Volume |
Statistical physics,Assortativity,Critical value,Betweenness centrality,Traffic dynamics,Complex network,Statistics,Classical mechanics,Spite,Mathematics,Eigenvalues and eigenvectors | Journal | 91 |
Issue | ISSN | Citations |
6 | 1539-3755 | 1 |
PageRank | References | Authors |
0.39 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Han-Xin Yang | 1 | 31 | 5.94 |
| Ming Tang | 2 | 103 | 10.22 |
| Ying-Cheng Lai | 3 | 315 | 35.67 |