Meeting Latency and Jitter Demands of Beyond 5G Networking Era: Are CNFs Up to the Challenge?

The introduction of Network Function Virtualization (NFV) has shifted network processing from specialized hardware to more flexible commodity servers, and this transition is still evolving. New industrial applications, the Internet of Things (IoT), and technologies like augmented, virtual, and mixed reality (AR/VR/MR) require networks that can handle event-based operations and middleware with very low and predictable latency. These requirements pose performance optimization challenges for packet processing in a layered infrastructure. In this study, we look deep into the challenges of implementing such network infrastructures using general-purpose hardware, a strategy motivated by its flexibility to realize telco-cloud and the potential to reduce electronic waste. Focusing on NFV with an emphasis on containerized network functions (CNFs), we investigate the performance limitations, particularly the high jitter and throughput variation observed in packet forwarding. We used a network function (NF) implemented using defacto industry standard user-space I/O architecture DPDK in bare-metal and containerized environments for performance evaluation. We conducted ten experiments in a 40 GbE environment to measure throughput, latency, and jitter across various packet sizes, traffic rates, and system configurations. The results indicate that adjusting CPU settings can significantly enhance throughput for CNFs despite a potential increase in jitter. We found that CNFs are feasible for latency-sensitive tasks, particularly under conditions of low traffic and specific packet sizes. With careful system-level configuration, CNFs can be used in beyond 5G cloud-native networking, offering promising potential for latency-sensitive applications.