Efficient routing on complex networks.

By G. Yan, Tao Zhou, Bo Hu, Zhong-Qian Fu, Bing-Hong Wang. Physical review. E, Statistical, nonlinear, and soft matter physics, 2005

543 citations recorded by the source corpus.

We propose a routing strategy to improve the transportation efficiency on complex networks. Instead of using the routing strategy for shortest path, we give a generalized routing algorithm to find the so-called efficient path, which considers the possible congestion in the nodes along actual paths. Since the nodes with the largest degree are very susceptible to traffic congestion, an effective way to improve traffic and control congestion, as our strategy, can be redistributing traffic load in central nodes to other noncentral nodes. Simulation results indicate that the network capability in processing traffic is improved more than 10 times by optimizing the efficient path, which is in good agreement with the analysis.

Subfields: Computational Theory and Mathematics, Geometry and Topology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/92ef06261496236482226de3ac2cdcfb3663b311

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In Computational Theory and Mathematics

In Geometry and Topology

In Statistical and Nonlinear Physics

Citations in the corpus

Vital nodes identification in complex networks (2016, background): “In addition to the possibly heterogeneous packet generating rates and link bandwidths [79], the dynamical features of network traffic are mainly determined by the routing table, which lists the paths through which a packet generated by a source node vs can be delivered to its target node vt [80].”
Identifying influential nodes in complex networks (2012, background): “Betweenness is, in some sense, a measure of the influence of a node over the information spread through the network or the expected load of a node in a transportation network [15,16].”
Link Prediction in Complex Networks: A Survey (2010, background): “13 The congestability refers to the maximal betweenness centrality which governs the transportation throughput of a network [134,135].”
Control Centrality and Hierarchical Structure in Complex Networks (2012, background): “networked transportation [40], synchronization [41] and epidemic spreading [42]).”