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 languageEnglish (US)
Article number062817
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume91
Issue number6
DOIs
StatePublished - Jun 29 2015

Fingerprint

Epidemic Spreading
traffic
Traffic
thresholds
Traffic Dynamics
Betweenness
Largest Eigenvalue
Mean-field Theory
Traffic Flow
Numerics
Complex Networks
Critical value
Directly proportional
Calculate
Predict
eigenvalues
Coefficient
coefficients
matrices

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Statistical and Nonlinear Physics
  • Statistics and Probability

Cite this

Traffic-driven epidemic spreading in correlated networks. / Yang, Han Xin; Tang, Ming; Lai, Ying-Cheng.

In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, Vol. 91, No. 6, 062817, 29.06.2015.

Research output: Contribution to journalArticle

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