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arXiv · 2310.06279

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

Shalini Choudhury·Sushovan Das·Sanjoy Paul·Prasanthi Maddala·Ivan Seskar·Dipankar Raychaudhuri
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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.

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Shalini Choudhury, Sushovan Das, Sanjoy Paul, Prasanthi Maddala, Ivan Seskar, Dipankar Raychaudhuri. 2023-10-10. MEC-Intelligent Agent Support for Low-Latency Data Plane in Private NextG Core. https://arxiv.org/abs/2310.06279

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