基于SDN和深度学习的自适应路由优化机制实验结果数据

该数据集主要面向SDN环境中自适应路由优化的研究，关注控制器的智能决策问题，使用RYU+mininet环境进行仿真实验，主要记录了时延、丢包率、吞吐量和链路利用率指标等仿真观测值，数据量33KB.

This dataset is primarily designed for research on adaptive routing optimization in Software-Defined Networking (SDN) environments, focusing on the intelligent decision-making issues of SDN controllers. Simulation experiments were conducted using the RYU and Mininet environments. It mainly records simulated observation metrics including delay, packet loss rate, throughput, and link utilization, with a total data size of 33 KB.

搜集汇总

背景与挑战

背景概述

该数据集记录了在SDN环境中，基于深度学习的自适应路由优化机制的仿真实验结果。数据来源于RYU+mininet仿真平台，主要包含时延、丢包率、吞吐量和链路利用率等网络性能指标。