### Literature Review
#### Research Status of Cascading Failure  
Due to the advancement of informatization, the number of nodes in various networks has doubled. Network topology has become more complex, making cascading failures more common. Cascading failures are commonly found in sensor networks [13; 14], transportation systems [15; 16; 17], and power systems [18; 19]. In sensor networks research on cascading failure, [PERSON] et al. [20] studied the topological characteristics of WSN based on complex network theory. The impact of different types of nodes on the invulnerability of sensor networks was analyzed from the perspective of the destructiveness of complex networks. [PERSON] et al. [21] proposed a new energy-efficient and fault-tolerant evolution model for large-scale wireless sensor networks based on complex network theory. In the evolution model, not only the residual energy of each node is considered, but also the link constraints are introduced to make the energy consumption of the whole network more balanced. [PERSON] et al. [22] established scale-free topology cascading failure networks. Then the cascading failure control method was proposed according to the critical load. [PERSON] et al. [23] divided the network load of wireless sensors into two types: link-oriented and node-oriented. Through cascading failure simulation, it was found that the minimum cost required to defend against intentional node attacks is more expensive than that required to face intentional link attacks. The research direction from sensor network cascading failure, in turn, is based chiefly on peer-to-peer planar structures and coupled networks [24]. Due to the lack of research on cascading failures in hierarchical topology, this research is very meaningful. Many research results have been obtained in the cascading failure model on overload research [25; 26; 27], evaluation mechanism [28; 29; 27], capacity definition [23], load redistribution [30; 31], and critical assessment [32; 28; 33]. These research results provide theoretical support for building healthy networks. In [28], a reasonable global load redistribution model was designed for communication networks, and it was found that the centrality can accurately reflect cascading failures. [PERSON] et al. [29] used two standard centrality metrics as a measure of network viability to assess the robustness of the network to vertex deletion, evaluated the advantages and disadvantages of network analysis techniques in assessing system architectures, and targeted guidelines for architecture robustness assessment. [PERSON] et al. [27] proposed a durability evaluation method based on the load-dependent overload model. It was found that network durability was strongly dependent on the initial disturbance strength and the cascading strength. Network durability with a uniform initial load distribution typically increases monotonically with decreasing initial disturbance strength. In contrast, durability behavior is more complex for other initial load distributions. [PERSON] et al. [31] studied the heterogeneous load-redistribution mechanism in a simplified sand-pile model. We find that weak heterogeneity in load redistribution can effectively mitigate cascades, while substantial heterogeneity in load redistribution can even enlarge the size of the final failure. [PERSON] et al. [34] introduced a self-healing model for overload propagation in complex networks caused by malicious attacks. We find that, during self-healing, the optimal recovery time for both the model and the real-world network exists within a given recovery resource. [PERSON] et al. [35] proposed an interdependent network cascading fault model based on mutual traffic redistribution under load fluctuations. In the model, the traffic loss related to the existing resources of the network is considered by defining the traffic-loss parameter. The results show that larger node tolerance and more significant flow loss parameters can improve network robustness.