SDN网络故障检测仿真数据

整体数据由西南交通大学于2020年5月产生，该成果通过细粒度划分故障类型，设计了一种基于SDN的数据中心故障恢复方案，经同行评议后发表于Electronics期刊上。实验产生的数据使用Python处理绘制。支撑论文“REVERT: A Network Failure Recovery Method for Data Center Networks”。

The entire dataset was generated by Southwest Jiaotong University in May 2020. This research conducted fine-grained fault type classification and designed a Software-Defined Networking (SDN)-based data center network failure recovery scheme, which was published in the journal Electronics after peer review. The experimental data were processed and visualized using Python. This dataset supports the paper titled "REVERT: A Network Failure Recovery Method for Data Center Networks".

搜集汇总

背景与挑战

背景概述

该数据集是西南交通大学于2020年5月生成的SDN网络故障检测仿真数据，用于支持发表在Electronics期刊上的论文'REVERT: A Network Failure Recovery Method for Data Center Networks'。数据集通过细粒度划分故障类型，设计了基于SDN的数据中心故障恢复方案，包含4个文件（格式为xlsx、pdf、docx），总数据量863.44KB，源自国家重点研发计划项目'新型光纤传输系统架构与关键技术研究'。