异构虚拟网络功能执行框架的性能优势研究

H. U. Adoga, Yehia El-khatib, D. Pezaros
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引用次数: 1

摘要

随着软件网络功能(NFs)的采用不断增长,我们评估了与各种加速和基于进程的NFV框架相比,支持sdn的数据平面实现的性能优势。典型的网络功能通过四种可选框架场景实现,即sdn感知软件交换机(数据平面)、虚拟机(VM)、数据平面开发工具包(DPDK) NF和容器化NF。我们的实验结果表明,数据平面的NF实现产生了更高的带宽和每秒数据包(pps)速率。在保持CPU利用率的情况下,获得的带宽比用户空间场景多14%。在我们的评估中,DPDK NFs可以在单个CPU核心上以更高的速率处理64B数据包,这是容器化NF实现的7倍,也绑定到单个核心上。我们的结果还显示了在异构框架上部署虚拟网络功能所带来的性能提升。
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On the Performance Benefits of Heterogeneous Virtual Network Function Execution Frameworks
As the adoption of softwarized network functions (NFs) keeps growing, we evaluate the performance benefits of SDN-aware data-plane implementations when compared to diverse acceleration and process-based NFV frameworks. Typical network functions have been implemented using four alternative frameworks scenarios, an SDN-aware software switch (data-plane), a virtual machine (VM), a Data-Plane Development Kit (DPDK) NF, and a containerized NF. Results from our experiments show that the data-plane NF implementation yields much higher bandwidth and packets per second (pps) rates. The bandwidth obtained is 14% more than the user-space scenario while retaining CPU utilization. The DPDK NFs in our evaluation can process packets at a much higher rate for 64B packets, on a single CPU core, which is 7 times higher than the containerized NF implementations, also tied to a single core. Our results also show the performance gains from deploying virtual network functions on heterogeneous frameworks.
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