摘要
针对复杂网络中相连节点之间的度相关性与病毒传播之间的关系,基于经典病毒传播模型SIS和SIR,研究了BA无尺度网络、ER随机网络及技术网络、社会网络等真实世界网络上的病毒传播行为。通过连续改变已知网络的度相关系数,来观察病毒传播的变化情况。仿真结果表明,异配网会络加速病毒的传播,而传播速度对同配网络具有更高的敏感性,且同配网络传播临界值较低。此外,目标免疫对异配网络具有更有效的免疫效果。
Spreading behaviour of BA scale-free network, ER random network and some real-world networks such as technic networks and social networks was investigated based on typical virus spreading model SIS and SIR. The vairations of virus spreading were observed via tuning the degree correlation of certain networks. Simulation result demonstrates that disassortativity accelerates virus spreading while speed is more sensitive to assortative networks, meanwhile, spreading threshold is lower in disassortative network. Besides that, the immunization strategy which faces at nodes with higher degrees is more efficient for disassortative networks.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2012年第8期1723-1727,1732,共6页
Journal of System Simulation
基金
国家自然科学基金资助项目(60973022)
关键词
度相关性
病毒传播
SIR模型
目标免疫
degree correlation
virus spreading
SIR model
target immunization
