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网络可靠性:局部网络结构对扩散过程的影响。

Network reliability: the effect of local network structure on diffusive processes.

作者信息

Youssef Mina, Khorramzadeh Yasamin, Eubank Stephen

机构信息

Network Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA.

Network Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA and Department of Physics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2013 Nov;88(5):052810. doi: 10.1103/PhysRevE.88.052810. Epub 2013 Nov 21.

Abstract

This paper reintroduces the network reliability polynomial, introduced by Moore and Shannon [Moore and Shannon, J. Franklin Inst. 262, 191 (1956)], for studying the effect of network structure on the spread of diseases. We exhibit a representation of the polynomial that is well suited for estimation by distributed simulation. We describe a collection of graphs derived from Erdős-Rényi and scale-free-like random graphs in which we have manipulated assortativity-by-degree and the number of triangles. We evaluate the network reliability for all of these graphs under a reliability rule that is related to the expected size of a connected component. Through these extensive simulations, we show that for positively or neutrally assortative graphs, swapping edges to increase the number of triangles does not increase the network reliability. Also, positively assortative graphs are more reliable than neutral or disassortative graphs with the same number of edges. Moreover, we show the combined effect of both assortativity-by-degree and the presence of triangles on the critical point and the size of the smallest subgraph that is reliable.

摘要

本文重新引入了由摩尔和香农[摩尔和香农,《富兰克林学会杂志》262, 191 (1956)]提出的网络可靠性多项式,用于研究网络结构对疾病传播的影响。我们展示了一种非常适合通过分布式模拟进行估计的多项式表示形式。我们描述了一组从厄多斯 - 雷尼随机图和类无标度随机图派生而来的图,在这些图中我们操纵了度的相关性和三角形的数量。我们根据与连通分量的预期大小相关的可靠性规则,评估所有这些图的网络可靠性。通过这些广泛的模拟,我们表明,对于正相关或中性相关的图,交换边以增加三角形的数量并不会提高网络可靠性。此外,在边数相同的情况下,正相关图比中性或负相关图更可靠。而且,我们展示了度的相关性和三角形的存在对临界点以及可靠的最小子图大小的综合影响。

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Emergence of scaling in random networks.随机网络中幂律分布的出现。
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