Moreno Yamir, Nekovee Maziar, Vespignani Alessandro
Departamento de Física Teórica, and Instituto de Biocomputación y Física de Sistemas Complejos, Universidad de Zaragoza, Zaragoza 50009, Spain.
Phys Rev E Stat Nonlin Soft Matter Phys. 2004 May;69(5 Pt 2):055101. doi: 10.1103/PhysRevE.69.055101. Epub 2004 May 21.
We study the dynamics of epidemic spreading processes aimed at spontaneous dissemination of information updates in populations with complex connectivity patterns. The influence of the topological structure of the network in these processes is studied by analyzing the behavior of several global parameters, such as reliability, efficiency, and load. Large-scale numerical simulations of update-spreading processes show that while networks with homogeneous connectivity patterns permit a higher reliability, scale-free topologies allow for a better efficiency.
我们研究旨在信息更新在具有复杂连接模式的人群中自发传播的流行病传播过程的动力学。通过分析几个全局参数(如可靠性、效率和负载)的行为,研究了网络拓扑结构在这些过程中的影响。更新传播过程的大规模数值模拟表明,虽然具有均匀连接模式的网络具有更高的可靠性,但无标度拓扑结构具有更好的效率。