Paths selection algorithms and rate adaptation objective functions are usually studied separately. In contrast, this paper evaluates some traffic engineering (TE) systems for software defined networking obtained by combining path selection techniques with average delay and load balancing, the two most popular TE objective functions. Based on TE simulation results, the best TE system suitable for software defined networks is a system where the paths are calculated using an oblivious routing model and its adaptation rate calculated using an average delay objective function. Thus, we propose the RACKE+AD system combining path sets computed using Räcke’s oblivious routing and a traffic splitting objective function using average delay. This model outperforms current state-of-the-art models, maximizes throughput, achieves better network resource utilization, and minimizes delay. The proposed system outperformed SMORE and SWAN by 4.2% and 9.6% respectively, achieving 27% better utilization and delivering 34% more traffic with 50% less latency compared with both systems on a GÉANT network.

通常分别研究路径选择算法和速率自适应目标函数。相比之下，本文对一些流量工程（TE）系统进行了评估，该系统通过结合具有两种最流行的TE目标功能的平均延迟和负载平衡的路径选择技术而获得，用于软件定义的网络。根据TE仿真结果，适用于软件定义网络的最佳TE系统是这样的系统，其中使用遗忘路由模型计算路径，并使用平均延迟目标函数计算其自适应率。因此，我们提出了RACKE + AD系统，该系统结合了使用Räcke的遗忘路由计算的路径集和使用平均延迟的流量分割目标函数。该模型优于当前的最新模型，可最大程度地提高吞吐量，实现更好的网络资源利用率，并最大程度地减少延迟。与GÉANT网络上的两个系统相比，拟议的系统的性能分别比SMORE和SWAN分别高4.2％和9.6％，利用率提高了27％，传输量增加了34％，延迟减少了50％。