Study of data center communication network topologies using complex network propagation model

Abstract

Data center, as the core infrastructure of data storage and processing, calls for network security protection. Information security has been addressed in a number of specific ways. However, there are few studies that employ network topology features to prevent the transmission of viruses. When a virus spreads, different topologies display various properties. In this paper, we study three types of data center network topologies, i.e., Fat-tree, Leaf-spine, and Bcube, and quantify the propagation characteristics in every topology through the IC propagation model. The probability of the device being infected, the count of propagation sources, the access of propagation sources, and the topological parameters are all considered. Given that network security defenders can only change the topology and topological parameters, we propose a computational framework that combines factor analysis, which provides us with the selection of network topological parameters with a low virus propagation rate in the candidate parameter set. Through experiments, we find that Leaf-spine has a good inhibitory effect on viruses with high propagation probability. Meanwhile, each offers unique advantages. We hope that more data center network topologies will be studied to improve the security of all data centers using these network topologies.