无标度网络中类扩散过程的鲁棒性和同化性
Robustness and Assortativity for Diffusion-like Processes in Scale-free Networks
摘要：
通过分析复杂网络中流行病和灾难的扩散动力学，研究了传染性对网络鲁棒性的影响。我们首先通过频谱分析确定阈值以上的流行病/故障可以传播，然后我们计算最慢的扩散时间。我们的研究结果表明，dispertative网络表现出更高的流行病学阈值，因此更容易免疫，而在dispertative网络有一个更长的时间进行干预之前，流行病/故障蔓延。此外，我们研究了沙堆级联模型，一个扩散模型的危机传播（金融传染）的计算机模拟。我们发现，虽然预防性网络更容易传播流行病/故障，度有针对性的免疫政策增加了他们的系统性风险的弹性。
英文摘要：
By analysing the diffusive dynamics of epidemics and of distress in complex networks, we study the effect of the assortativity on the robustness of the networks. We first determine by spectral analysis the thresholds above which epidemics/failures can spread; we then calculate the slowest diffusional times. Our results shows that disassortative networks exhibit a higher epidemiological threshold and are therefore easier to immunize, while in assortative networks there is a longer time for intervention before epidemic/failure spreads. Moreover, we study by computer simulations the sandpile cascade model, a diffusive model of distress propagation (financial contagion). We show that, while assortative networks are more prone to the propagation of epidemic/failures, degree-targeted immunization policies increases their resilience to systemic risk.
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