Epidemic Processes Over Time-Varying Networks

被引：82
|
作者：
Pare, Philip E. [1 ]
Beck, Carolyn L. [1 ]
Nedic, Angelia [2 ]
机构：
[1] Univ Illinois, Coordinated Sci Lab, Urbana, IL 61801 USA
[2] Arizona State Univ, Sch Elect Comp & Energy Engn, Tempe, AZ 85281 USA
来源：
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS | 2018年 / 5卷 / 03期
基金：
美国国家科学基金会;
关键词：
Epidemic processes; Networked systems; Stochastic systems; Time-varying systems; SUFFICIENT CONDITIONS; STABILITY; MODELS; THRESHOLD; SPREAD; GRAPHS;
D O I：
10.1109/TCNS.2017.2706138
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The spread of viruses in biological networks, computer networks, and human contact networks can have devastating effects; developing and analyzing mathematical models of these systems can provide insights that lead to long-term societal benefits. Prior research has focused mainly on network models with static graph structures; however, the systems being modeled typically have dynamic graph structures. In this paper, we consider virus spread models over networks with dynamic graph structures, and we investigate the behavior of these systems. We perform a stability analysis of epidemic processes over time-varying networks, providing sufficient conditions for convergence to the disease-free equilibrium (the origin, or healthy state), in both the deterministic and stochastic cases. We present simulation results and discuss quarantine control via simulation.
引用
收藏
页码：1322 / 1334
页数：13
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