Congestion-gradient driven transport on complex networks
<|reference_start|>Congestion-gradient driven transport on complex networks: 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.<|reference_end|>
@article{danila2006congestion-gradient,
    title={Congestion-gradient driven transport on complex networks},
    author={Bogdan Danila, Yong Yu, Samuel Earl, John A. Marsh, Zoltan Toroczkai,
  and Kevin E. Bassler},
    journal={Phys Rev E 74, 046114 (2006)},
    year={2006},
    doi={10.1103/PhysRevE.74.046114},
    archivePrefix={arXiv},
    eprint={cond-mat/0603861},
    primaryClass={cond-mat.stat-mech cond-mat.dis-nn cs.NI}
}