title: Traffic-driven epidemic spreading in correlated networks.
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.
authors.affiliation: Department of Physics, Fuzhou University, Fuzhou 350108, China.
authors.forename: Han-Xin
authors.initials: HX
authors.lastname: Yang
authors.affiliation: Web Sciences Center, University of Electronic Science and Technology of China, Chengdu 610051, China.
authors.forename: Ming
authors.initials: M
authors.lastname: Tang
authors.affiliation: School of Electrical, Computer and Energy Engineering, Arizona State University, Arizona 85287, USA.
authors.forename: Ying-Cheng
authors.initials: YC
authors.lastname: Lai