Optimizing Edge Gaming Slices through an Enhanced User Plane Function and Analytics in Beyond-5G Networks

TL;DR

This paper presents a novel architecture integrating NWDAF and UPF with AI to improve latency measurement and management in edge gaming within beyond-5G networks, enhancing user experience and service quality.

Contribution

It introduces a closed-loop architecture combining NWDAF and UPF with AI for non-intrusive latency estimation and control plane enhancement in edge gaming.

Findings

AI-enabled game classification improves latency management.

Embedding analytics in UPF enhances service-level compliance.

Latency-aware control plane optimizes edge gaming performance.

Abstract

The latest generation of games and pervasive communication technologies poses challenges in service management and Service-Level Agreement compliance for mobile users. State-of-the-art edge-gaming techniques enhance throughput, reduce latency, and leverage cloud computing. However, further development of core functions such as the User Plane Function (UPF) is needed for non-intrusive user latency measurement. This paper proposes a closed-loop architecture integrating the Network Data Analytics Function (NWDAF) and UPF to estimate user latency and enhance the 5G control plane by making it latency-aware. The results show that embedding an artificial intelligence model within NWDAF enables game classification and opens new avenues for mobile edge gaming research.