Towards optimal adaptation of NFV packet processing to modern CPU memory architectures

ABSTRACT

Network Functions Virtualization (NFV) aims to move network functions away from expensive hardware appliances to off-the-shelf server hardware. NFV promises higher flexibility and cost reduction for the network operator. In order to achieve high throughput performance with this commodity hardware, fast packet processing frameworks like NetMap or the Data Plane Development Kit (DPDK) can be used. It is known that packet processing performance is very sensitive regarding copying of packets. In this paper we take steps towards quantifying the efficiency of NFV regarding packet copying overhead at hardware level. As modern servers are often built up of multiple CPUs with segregated memory, we evaluate the performance penalties resulting from this segregation in conjunction with DPDK. Additionally we evaluate the effects of cache misses on packet processing in detail. Subsequently a metric that quantifies the efficiency of a running VNF is introduced and an optimization scheme is outlined which describes the use of the metric. Our results show how both cache misses and memory segregation reduce the network efficiency.

References

1. Amitabha Banerjee, Rishi Mehta, and Zach Shen. 2015. NUMA Aware I/O in Virtualized Systems. In IEEE 23rd Annual Symposium on High-Performance Interconnects (HOTI). IEEE.
2. Ivano Cerrato, Mauro Annarumma, and Fulvio Risso. 2014. Supporting fine-grained network functions through Intel DPDK. In Third European Workshop on Software Defined Networks (EWSDN). IEEE.
3. Mihai Dobrescu, Katerina Argyraki, and Sylvia Ratnasamy. 2012. Toward Predictable Performance in Software Packet-Processing Platforms. In Proceedings of NSDI 12. USENIX.
4. Dr. David Levinthal PhD. - Intel. 2009. Performance Analysis Guide for Intel Core i7 Processor and Intel Xeon 5500 processors.
5. ETSI. 2012. Network Functions Virtualisation - Introductory White Paper. SDN and OpenFlow World Congress (2012).
6. John L. Hennessy and David A. Patterson. 2012. Computer Architecture a Quantitative Approach Fifth Edition.
7. Yang Hu and Tao Li. 2016. Towards efficient server architecture for virtualized network function deployment: Implications and implementations. In 49th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).
8. Ryota KAWASHIMA and Hiroshi MATSUO. 2017. A Generic and Efficient Local Service Function Chaining Framework for User VM-dedicated Micro-VNFs. IEICE Transactions on Communications (2017).
9. Sameer G Kulkarni, Wei Zhang, Jinho Hwang, et al. 2017. NFVnice: Dynamic Backpressure and Scheduling for NFV Service Chains. In Proceedings of the Conference of the ACM Special Interest Group on Data Communication, SIGCOMM '17. ACM.
10. Peilong Li, Xiaoban Wu, Yongyi Ran, and Yan Luo. 2017. Designing Virtual Network Functions for 100 GbE Network Using Multicore Processors. (2017).
11. Marek Majkowski. 2015. Cloudflare Blog: How to receive a million packets per second. (2015). https://blog.cloudflare.com/how-to-receive-a-million-packets/
12. Bryan Veal and Annie Foong. 2007. Performance scalability of a multi-core web server. In Proceedings of the 3rd ACM/IEEE Symposium on Architecture for networking and communications systems. ACM.
13. Chengwei Wang, Oliver Spatscheck, and Vijay et al. Gopalakrishnan. 2016. Toward High-Performance and Scalable Network Functions Virtualization. IEEE Internet Computing (2016).

Index Terms

• Computer systems organization

  • Dependable and fault-tolerant systems and networks

    • Processors and memory architectures

• Networks

  • Network components

    • End nodes

      • Network servers

  • Network performance evaluation

    • Network performance analysis