MEC-Intelligent Agent Support for Low-Latency Data Plane in Private NextG Core

TL;DR

This paper introduces MEC-IA, a centralized agent that dynamically manages resources in private 5G data planes, significantly reducing latency and improving resource efficiency for critical applications.

Contribution

It proposes a novel MEC-IA framework for proactive resource distribution in private 5G UPFs, extending to MEC layers for further latency reduction.

Findings

Reduces worst-case latency by up to 77.8% under skewed uRLLC traffic.

Increases uRLLC connectivity gain by 2.40 times.

Achieves 40% CapEx savings.

Abstract

Private 5G networks will soon be ubiquitous across the future-generation smart wireless access infrastructures hosting a wide range of performance-critical applications. A high-performing User Plane Function (UPF) in the data plane is critical to achieving such stringent performance goals, as it governs fast packet processing and supports several key control-plane operations. Based on a private 5G prototype implementation and analysis, it is imperative to perform dynamic resource management and orchestration at the UPF. This paper leverages Mobile Edge Cloud-Intelligent Agent (MEC-IA), a logically centralized entity that proactively distributes resources at UPF for various service types, significantly reducing the tail latency experienced by the user requests while maximizing resource utilization. Extending the MEC-IA functionality to MEC layers further incurs data plane latency reduction. Based on our extensive simulations, under skewed uRLLC traffic arrival, the MEC-IA assisted bestfit UPF-MEC scheme reduces the worst-case latency of UE requests by up to 77.8% w.r.t. baseline. Additionally, the system can increase uRLLC connectivity gain by 2.40x while obtaining 40% CapEx savings.