Accelerating Virtual Network Functions With Fast-Slow Path Architecture Using eXpress Data Path

Abstract

By decoupling network functions from dedicated, proprietary hardware network devices, Network Function Virtualization (NFV) allows building Virtual Network Functions (VNFs) that can run on standard, commodity servers to reduce cost and gain flexibility in network deployment, operation, and management. However, building VNFs with high-throughput and low-latency is a big challenge. In this paper, we propose eVNF - a hybrid fast-slow path architecture to build and accelerate VNFs with eXpress Data Path (XDP), which is a Linux kernel framework that enables high performance and programmable network processing. The programmability of XDP is limited to ensure kernel safety, thus causing difficulties when using XDP to accelerate VNFs. eVNF solves this problem by taking a hybrid approach: leave the simple but critical tasks inside the kernel with XDP, and let complex tasks be processed outside XDP, e.g., in user-space. With the hybrid architecture, eVNF allows building fast and flexible VNFs. We applied eVNF to build four prototype VNFs: Flow Monitoring (eFM), Firewall (eFW), Deep Packet Inspection (eDPI), and Load Balancer (eLB). These VNFs are evaluated individually and in service function chains (SFCs) using OpenStack. Our experiments showed that eVNF can significantly improve service throughput as well as reduce latency and CPU usage. eVNF-based VNFs also can scale out with the number of CPU cores and can combine with Open vSwitch - Data Plane Development Kit (OvS-DPDK) for better performance.