Modeling the coevolution of topology and traffic on weighted technological networks.
Modeling the coevolution of topology and traffic on weighted technological networks.
复制标题
DOI：
10.1103/physreve.75.026111
复制
发表时间：
2007-02
期刊：
影响因子：
--
通讯作者：
Yan-Bo Xie;Wenxu Wang;B. Wang
中科院分区：
文献类型：
--
作者：
Yan-Bo Xie;Wenxu Wang;B. Wang
对于许多技术网络来说，网络结构和其上发生的流量是相互作用的。流量增长的需求刺激着网络的演进和增长，以维持其正常、高效的运行。同时，网络结构的变化导致流量的重新分配。在本文中，我们进行了广泛的数值和分析研究，扩展了 Wang [Phys.莱特牧师。 94, 188702 (2005)]。通过引入由任意一对顶点之间的流量增量驱动的一般强度耦合交互，我们的模型生成强度、权重和度的无标度分布网络。特别是，所获得的顶点强度和度之间的非线性相关性以及不协调特性表明该模型能够表征加权技术网络。此外，生成的图具有密集的聚类结构以及顶点聚类和度之间的反相关性，这在现实世界的网络中广泛观察到。相应的理论预测与仿真结果很好地吻合。
For many technological networks, the network structures and the traffic taking place on them mutually interact. The demands of traffic increment spur the evolution and growth of the networks to maintain their normal and efficient functioning. In parallel, a change of the network structure leads to redistribution of the traffic. In this paper, we perform an extensive numerical and analytical study, extending results of Wang [Phys. Rev. Lett. 94, 188702 (2005)]. By introducing a general strength-coupling interaction driven by the traffic increment between any pair of vertices, our model generates networks of scale-free distributions of strength, weight, and degree. In particular, the obtained nonlinear correlation between vertex strength and degree, and the disassortative property demonstrate that the model is capable of characterizing weighted technological networks. Moreover, the generated graphs possess both dense clustering structures and an anticorrelation between vertex clustering and degree, which are widely observed in real-world networks. The corresponding theoretical predictions are well consistent with simulation results.