Effects of Social Network Structure on Epidemic Disease Spread Dynamics with Application to Ad Hoc Networks

被引:11
作者
Guizani, Nadra [1 ]
Elghariani, Ali [2 ]
Kobes, Jason [1 ]
Ghafoor, Arif [2 ]
机构
[1] Purdue Univ, W Lafayette, IN 47907 USA
[2] Purdue Univ, Sch Elect & Comp Engn, W Lafayette, IN 47907 USA
来源
IEEE NETWORK | 2019年 / 33卷 / 03期
基金
美国国家科学基金会;
关键词
Analytical models; Biological system modeling; Computational modeling; Diseases; Mathematical model; Sociology; Statistics;
D O I
10.1109/MNET.2019.1800026
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
With the frequent appearance and spread of infectious diseases and their impact on major population areas, there is a growing interest to develop models for analyzing the dynamic behavior of epidemics. Such analysis can provide a better decision making process to combat and confine disease. In this article, we briefly survey the literature on network structure effect on disease spread models. Subsequently, we discuss an SEIR based epidemic model for different levels of aggregation of population. This model is subsequently applied to analyze virus propagation phenomena in mobile ad hoc networks. For managing this type of threat, we propose two security architectures for these networks based on several design criteria including scalability, power, and computation limitations.
引用
收藏
页码:139 / 145
页数:7
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