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优化面向交通驱动型传染病传播的保护资源分配。

Optimizing protection resource allocation for traffic-driven epidemic spreading.

机构信息

School of Mathematics, Southeast University, Nanjing 210096, People's Republic of China.

School of Physics, Hefei University of Technology, Hefei 230009, People's Republic of China.

出版信息

Chaos. 2022 Aug;32(8):083141. doi: 10.1063/5.0098384.

Abstract

Optimizing the allocation of protection resources to control the spreading process in networks is a central problem in public health and network security. In this paper, we propose a comprehensive adjustable resource allocation mechanism in which the over allocation of resources can be also numerically reflected and study the effects of this mechanism on traffic-driven epidemic spreading. We observe that an inappropriate resource allocation scheme can induce epidemic spreading, while an optimized heterogeneous resource allocation scheme can significantly suppress the outbreak of the epidemic. The phenomenon can be explained by the role of nodes induced by the heterogeneous network structure and traffic flow distribution. Theoretical analysis also gives an exact solution to the epidemic threshold and reveals the optimal allocation scheme. Compared to the uniform allocation scheme, the increase in traffic flow will aggravate the decline of the epidemic threshold for the heterogeneous resource allocation scheme. This indicates that the uneven resource allocation makes the network performance of suppressing epidemic degrade with the traffic load level. Finally, it is demonstrated that real-world network topology also confirms the results.

摘要

优化保护资源的分配以控制网络中的传播过程是公共卫生和网络安全的核心问题。在本文中,我们提出了一种全面的可调节资源分配机制,其中也可以数值反映资源的过度分配,并研究该机制对流量驱动的传染病传播的影响。我们观察到,不适当的资源分配方案会导致传染病的传播,而优化的异质资源分配方案可以显著抑制传染病的爆发。这种现象可以通过异质网络结构和流量分布引起的节点作用来解释。理论分析还为传染病阈值给出了精确解,并揭示了最优分配方案。与均匀分配方案相比,异质资源分配方案中流量的增加会加剧传染病阈值的下降。这表明,不均匀的资源分配会随着流量负载水平的变化而降低网络抑制传染病的性能。最后,还证明了真实网络拓扑也证实了这一结果。

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