Scaling behavior of an artificial traffic model on scale-free networks
Shi-Min Cai, Gang Yan, Tao Zhou, Pei-Ling Zhou, Zhong-Qian Fu, Bing-Hong Wang
Abstract
In this article, we investigate an artificial traffic model on scale-free networks. Instead of using the routing strategy of the shortest path, a generalized routing algorithm is introduced to improve the transportation throughput, which is measured by the value of the critical point disjoining the free-flow phase and the congested phase. By using the detrended fluctuation analysis, we found that the traffic rate fluctuation near the critical point exhibits the 1/f-type scaling in the power spectrum. The simulation results agree very well with the empirical data, thus the present model may contribute to the understanding of the underlying mechanism of network traffics.
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