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Congestion-gradient driven transport on complex networks

Bogdan Danila·Yong Yu·Samuel Earl·John A. Marsh·Zoltan Toroczkai·Kevin E. Bassler
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Abstract

We present a study of transport on complex networks with routing based on local information. Particles hop from one node of the network to another according to a set of routing rules with different degrees of congestion awareness, ranging from random diffusion to rigid congestion-gradient driven flow. Each node can be either source or destination for particles and all nodes have the same routing capacity, which are features of ad-hoc wireless networks. It is shown that the transport capacity increases when a small amount of congestion awareness is present in the routing rules, and that it then decreases as the routing rules become too rigid when the flow becomes strictly congestion-gradient driven. Therefore, an optimum value of the congestion awareness exists in the routing rules. It is also shown that, in the limit of a large number of nodes, networks using routing based on local information jam at any nonzero load. Finally, we study the correlation between congestion at node level and a betweenness centrality measure.

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Bogdan Danila, Yong Yu, Samuel Earl, John A. Marsh, Zoltan Toroczkai, Kevin E. Bassler. 2006-03-31. Congestion-gradient driven transport on complex networks. https://doi.org/10.1103/physreve.74.046114

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