@article{Zhou2023, 
author = {Bin Zhou and Xiujuan Ma and Fuxiang Ma and Shujie Gao},
title = {Robustness analysis of random hyper-networks based on the internal structure of hyper-edges},
year = {2023},
journal = {AIMS Mathematics},
volume = {8},
number = {2},
pages = {4814-4829},
keywords = {robustness, cascading failures, random hyper-networks, internal structure of hyper-edges, capacity-load model},
url = {https://www.sciopen.com/article/10.3934/math.2023239},
doi = {10.3934/math.2023239},
abstract = {Random hyper-network is an important hyper-network structure. Studying the structure and properties of random hyper-networks, which helps researchers to understand the influence of the hyper-network structure on its properties. Currently, studies related to the influence of the internal structure of the hyper-edge on robustness have not been carried out for research on the robustness of hyper-networks. In this paper, we construct three    k-uniform random hyper-networks with different structures inside hyper-edges. The nodes inside hyper-edges are connected in the ways randomly connected, preferentially connected and completely connected. Meanwhile, we propose a capacity-load model that can describe the relationship between the internal structure and the robustness of the hyper-edge, based on the idea of capacity-load model. The robustness of the three hyper-networks was obtained by simulation experiments. The results show the variation of the internal structure of hyper-edge has a large influence on the robustness of the    k-uniform random hyper-network. In addition, the larger number of ordinary edges        m          k       inside the hyper-edges and the size of the hyper-network    k, the more robust the    k-uniform random hyper-network is.}
}