数学理论与应用 ›› 2025, Vol. 45 ›› Issue (3): 107-124.doi: 10.3969/j.issn.1006-8074.2025.03.006

• • 上一篇    

基于多层网络层内和层间结构的级联故障研究

陈梦姣;王妞;魏代俊*   

  1. 湖北民族大学数学与统计学院, 恩施, 445000
  • 出版日期:2025-09-28 发布日期:2025-11-07

Study on Cascading Failures Based on Intra-Layer and Inter-Layer Structures of Multiplayer Networks

CHEN Mengjiao; WANG Niu;WEI Daijun*   

  1. School of Mathematics and Statistics, Hubei Minzu University, Enshi 445000, China
  • Online:2025-09-28 Published:2025-11-07
  • Supported by:
    This work is supported by the National Social Science Fund Project (No. 23\&ZD115) and the Graduate Student Research Innovation Project of the School of Mathematics and Statistics, Hubei Minzu University (No. STK2023011)

摘要: 相较于单层网络,多层网络节点度构成更复杂,含层内度与层间度,但当前多层网络研究较少关注不同度对级联失效的影响.而区分其影响对理解网络结构、信息传播及行为预测具有意义. 本文提出一种容量负载模型, 用于研究并区分层内度与层间度对多层网络级联故障的影响. 通过设计基于节点总度、层内度好层间度的三种节点移除策略, 在四类典型网络中进行模拟实验, 以网络可承受的最大移除节点数目作为鲁棒性评价指标, 分析耦合系数、负载与容量调节参数对网络鲁棒性的影响. 实验结果表明, 在不同类型网络中, 对级联故障影响最小的节点移除策略存在差异, 反映出不同节点度在故障传播中所起作用的重要性. 与其他模型相比,本文所提模型能使网络在级联失效过程中保持更高的最大可移除节点数目, 显示出更优的鲁棒性.

关键词: 多层网络, 鲁棒性, 级联失效, 容量负载模型

Abstract: Compared to single-layer networks, multilayer networks exhibit a more complex node degree composition, comprising both intra-layer and inter-layer degrees. However, the distinct impacts of these degree types on cascading failures remain underexplored. Distinguishing their effects is crucial for a deeper understanding of network structure, information propagation, and behavior prediction. This paper proposes a capacity-load model to influence and compare the influence of different degree types on cascading failures in multilayer networks. By designing three node removal strategies based on total degree, intra-layer degree, and inter-layer degree, simulation experiments are conducted on four types of networks. Network robustness is evaluated using the maximum number of removable nodes before collapse. The relationships between network robustness and the coupling coefficient, as well as load and capacity adjustment parameters, are also analyzed. The results indicate that the node removal strategy with the least impact on cascading failures varies across different types of networks, revealing the significance of different node degrees in failure propagation. Compared to other models, the proposed model enables networks to maintain a higher maximum number of removable nodes during cascading failures, demonstrating superior robustness.

Key words: Multilayer network, Robustness, Cascading failure, Capacity load model