稀疏模块网络中信息业务的干扰和相关模式
Jamming and Correlation Patterns in Traffic of Information on Sparse Modular Networks
摘要：
研究了具有无标度子图的稀疏模块网络上的高密度信息流。通过不同的统计方法，我们区分了自由流和拥塞状态，并指出了模块在拥塞过渡中的作用。我们进一步考虑在网络中的每个节点收集的交通信号之间的相关性。信号对之间的相关矩阵反映了网络特征值谱的模块性和特征向量的结构。模块的内部结构在扩散动力学中具有重要作用，导致模块化枢纽之间的相关性增强，这不能通过标准方法过滤掉。讨论了具有未知模块结构的真实网络分析的意义。
英文摘要：
We study high-density traffic of information packets on sparse modular networks with scale-free subgraphs. With different statistical measures we distinguish between the free flow and congested regime and point out the role of modules in the jamming transition. We further consider correlations between traffic signals collected at each node in the network. The correlation matrix between pairs of signals reflects the network modularity in the eigenvalue spectrum and the structure of eigenvectors. The internal structure of the modules has an important role in the diffusion dynamics, leading to enhanced correlations between the modular hubs, which can not be filtered out by standard methods. Implications for the analysis of real networks with unknown modular structure are discussed.
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