摘要
本文通过分析谣言短信传播的特点以及方式,把谣言短信的传播过程抽象成一个网络的生长过程。根据谣言短信传播的特点,以星形网络表示初始网络,在局域世界中选择新增节点的连接节点。局域世界的选取,采用了依据节点之间的网络路径值作为选取局域世界的原则。给出了生成谣言短信传播网络模型的算法,并且通过理论推导说明网络模型的度分布为幂律函数,模拟了网络节点的度分布、聚类系数和平均路径长度,通过GN算法对模型的社团结构进行分析,发现谣言短信传播网络具有明显的社团结构特征。仿真结果表明,谣言短信传播网络同时具有具有无标度特性、小世界特性以及明显的社团结构特征。
社团结构是反映网络结构整体性质的重要特征,网络的稳定性和健壮性在很大程度上取决于网络的社团结构特征。通过在具有不同的社团结构的信息传播网络模型上,对网络进行相继故障仿真,研究社团结构对信息传播网络稳定性影响。为此,设计开发了复杂网络综合仿真平台。利用复杂网络仿真平台,改变信息网络的社团结构强度,从而形成不同社团结构强度的信息网络。再利用改进的节点动态相继故障模型,对不同社团结构强度信息网络进行故障传播过程模拟;研究网络在不同的社团结构强度下,网络的稳定性和健壮性。仿真结果表明,网络的稳定性和健壮性是随着社团结构之间链接紧密程度的增加,先减弱再增强,存在一个与网络规模、容差系数有关的临界值。
最后,对研究工作做出了总结,并对课题的进一步研究进行了展望。
The characteristic and the way of rumor short message propagation are analyzed in view of the course of the rumor short message propagation as networks growth. The initial network is star like, and the link nodes connected with the new added one are chosen in the local world. The selection of the local world depends on the value of network path between nodes. Model generating algorithm of rumor short message propagation networks is suggested. Degree distribution, clustering coefficient along with average path length are analyzed. Simulation result shows that the rumor short message propagation network has both small-world and scale-free property with clear community structure.
Community structure not only reflects the important characteristics of overall structure properties of networks, but also it determines the stability and the robustness to a large extent. As a result, on the different network modes of community structures’message propagation, network casecade failure simulation has been carried out to study community structures which affect the stability of the message propagation network. To this end, the complex network simulation platform has been designed. By the platform, the different community structures network are generated. On the base of improved node dynamic cascading failure model, Cascading failure on the message propagation networks was investigated. To the different density values of community structures, the stability of networks was explored, respectively. Simulation result shows that the stability of networks weakened at first and then enhanced with the increase of the community structures density value, and there was threshold value which was related with the scale and capacity coefficient of networks.
Finally, a summary about this theory is given, and a further prospect about this theme is offered.
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