Network failure model based on time series

作者：Yan Yu-Wei; Jiang Yuan^*; Yang Song-Qing; Yu Rong-Bin; Hong Cheng

来源：Acta Physica Sinica, 2022, 71(8): 088901.

DOI：10.7498/aps.71.20212106

• time series
• cascading failure
• robustness

With the development of network science, the static network has been unable to clearly characterize thedynamic process of the network. In real networks, the interaction between individuals evolves rapidly over time.This network model closely links time to interaction process. Compared with static networks, dynamic networkscan clearly describe the interaction time of nodes, which has more practical significance. Therefore, how tobetter describe the behavior changes of networks after being attacked based on time series is an importantproblem in the existing cascade failure research. In order to better answer this question, a failure model basedon time series is proposed in this paper. The model is constructed according to time, activation ratio, number ofedges and connection probability. By randomly attacking nodes at a certain time, the effects of four parameterson sequential networks are analyzed. In order to validate the validity and scientificity of this failure model, weuse small social networks in the United States. The experimental results show that the model is feasible. Themodel takes into account the time as well as the spreading dynamics and provides a reference for explaining thedynamic networks in reality.

• 单位
  y; 南昌航空大学; 中国人民解放军信息工程大学