Automatic Performance-Optimal Offloading of Network Functions on Programmable Switches

Abstract

In network function virtualization (NFV), network functions (NFs) are chained as a service function chain (SFC) to enhance NF management with low cost and high flexibility. Recent NFV solutions indicate that the packet processing performance of SFCs can be significantly improved by offloading NFs to programmable switches. However, such offloading requires a deep understanding of heterogeneous NF properties (e.g., resource consumption) to achieve the maximum SFC performance. Unfortunately, none of existing solutions provide automatic analysis of NF properties. Thus, network administrators have to manually examine the source codes of NFs and profile various NF properties, which is time-consuming and laborious. In this paper, we propose LightNF, a system that simplifies NF offloading in programmable networks. LightNF automatically dissects comprehensive NF properties by means of code analysis and performance profiling while eliminating manual efforts. It then leverages its analysis results of NF properties in its SFC placement so as to make the performance-optimal offloading decisions. We have implemented LightNF on Tofino-based hardware programmable switches. We perform extensive experiments to evaluate LightNF with a real-world testbed and large-scale simulation. Our experiments show that LightNF outperforms state-of-the-art solutions with an orders-of-magnitude reduction in per-packet processing latency and 9.5 improvement in SFC throughput.