DPI-powered application awareness
for 5G UPFs

Real-time network traffic insights for 5G UPFs

The 5G User Plane Function (5G UPF), a key component of 5G’s Service Based Architecture (SBA) and Control and User Plane Separation (CUPS) strategy, interconnects the data network and undertakes the role of identifying, aggregating, routing and forwarding user traffic. The 5G UPF delivers decentralized, high-throughput processing of traffic flows, allowing latency-sensitive applications such as autonomous driving to be processed in 5G edge networks instead of being backhauled to the 5G core. As you might expect, these complex 5G networks come with a number of performance challenges:

• Huge data volumes: With streaming of music and videos continuously growing in popularity, 5G networks need to keep up with the demand and support significantly higher data rates. This requires UPFs to handle large volumes of data traffic while maintaining high-throughput at the same time.
• Low latency: Particularly when it comes to critical applications like remote surgery, 5G networks need to provide low latency communication. UPFs need to process the relevant 5G packets with minimum delay (less than 1 millisecond latency).
• Sensitive user data: 5G networks come with more access points and network edges, which means more entry points for attacks and unwanted data flows. As part of a robust security system, the UPF is designed to handle sensitive user data and is crucial in identifying malicious traffic.
• Network slicing: Another challenge for UPFs is the different requirements, resource allocations and traffic patterns that come with different network slices. In order to meet the respective demands, manage the network and handle functioning challenges, a high-performance DPI solution is required.

By embedding deep packet inspection (DPI) into your security system, you can boost your 5G UPFs, improve the overall performance of 5G networks and enable high throughput and application-awareness. Real-time traffic intelligence through deep packet inspection plays a crucial role in supporting a wide range of traffic-aware functions offered by the 5G User Plane Function, both in core and edge networks, as the breadth of application types and customer demand for highly adaptable networking instances continue to grow. DPI allows you to steer 5G UPF traffic based on the application type, helping you to make efficient use of network resources thanks to greater application awareness.

Speed up 5G core and edge processing with DPI-driven real-time application visibility

Advanced packet-level and flow-level analysis with the cutting-edge DPI engines R&S®vPACE and R&S®PACE 2 by ipoque allow you to determine the traffic performance of different network slices, applications, sessions and users with real-time analyses of bandwidth, throughput, latency, speeds, jitter and packet loss. Application classification capabilities provided by R&S®vPACE and R&S®PACE 2 equip 5G UPFs with highly accurate, granular insights on different applications, protocols and services navigating 5G networks. Through leveraging advanced techniques like machine learning, deep learning and high-dimensional data analysis, you can detect flows which are obfuscated, encrypted and anonymized, increasing visibility into encrypted 5G traffic. These insights extend to IoT endpoints and user devices as well as cell sites and RAN nodes. By offloading UPF’s packet inspection functionality to R&S®PACE 2 and R&S®vPACE, you can leverage our threat intelligence to identify traffic flows which are malicious and suspicious alongside applications and devices that are compromised, while keeping tabs on anomalies and irregularities across any given traffic session.

A DPI-enabled 5G UPF with application visibility enables

• Application and subscriber-based routing and forwarding policies
• Dynamic instantiation of network slices using real-time application, subscriber and traffic intelligence
• Efficient and faster orchestration of CNFs and VNFs
• Superior QoS management via application-based prioritization and optimization policies
• Enhanced charging and usage reporting with fine-grained traffic information
• AI-based network slice automation
• Detection of malicious and fraudulent activity as well as abuse of network resources