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arxiv: 1503.00149 · v1 · pith:ZQTIQ5GWnew · submitted 2015-02-28 · ⚛️ physics.soc-ph · cs.SI

Suppressing traffic-driven epidemic spreading by edge-removal strategies

classification ⚛️ physics.soc-ph cs.SI
keywords epidemicedgesnodesspreadingtraffic-drivenfindlarge-degreenetwork
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The interplay between traffic dynamics and epidemic spreading on complex networks has received increasing attention in recent years. However, the control of traffic-driven epidemic spreading remains to be a challenging problem. In this Brief Report, we propose a method to suppress traffic-driven epidemic outbreak by properly removing some edges in a network. We find that the epidemic threshold can be enhanced by the targeted cutting of links among large-degree nodes or edges with the largest algorithmic betweeness. In contrast, the epidemic threshold will be reduced by the random edge removal. These findings are robust with respect to traffic-flow conditions, network structures and routing strategies. Moreover, we find that the shutdown of targeted edges can effectively release traffic load passing through large-degree nodes, rendering a relatively low probability of infection to these nodes.

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