The 5G Core User Plane Function is responsible for packet forwarding, GTP-U decapsulation, and quality of service enforcement for every user data session. How the UPF behaves under simultaneous multi-slice workloads remains empirically uncharacterised in the open literature. Specifically, how its forwarding latency responds to load, how well it isolates one slice from another, and what timing budgets remain available for intelligent control are all open questions. This paper presents a measurement study conducted on a containerised open5GS deployment with three concurrent network slices. We design and implement a namespace-aware TC-BPF instrumentation framework that resolves the fundamental obstacle preventing existing tools from attributing latency observations to individual containerised network functions. We deploy eMBB, URLLC, and mMTC slices with realistic application traffic under light, medium, and heavy load conditions and collect approximately 28 million matched N3 to N6 forwarding delay pairs. The gathered results reveal that eMBB forwarding delay is load-sensitive with the 99th percentile growing from 574 to 1,243 microseconds across load conditions. URLLC delay is load-insensitive, confirming per-UPF process isolation. mMTC exhibits wide-tail TCP behaviour. On this platform, N4 PFCP session modification latency remains consistently below 200 microseconds regardless of data-plane load, suggesting substantial timing headroom within the two-millisecond budget assumed by AI-driven UPF orchestration designs. The instrumentation framework, experiment scripts, and dataset schema are released at https://github.com/MP-Akhil-5G/open5gs-slice-measurement.

翻译：5G核心网用户面功能负责每个用户数据会话的数据包转发、GTP-U解封装和服务质量保障。现有文献尚未通过实验表征UPF在多切片并发负载下的行为特性，特别是其转发时延对负载的响应、切片间的隔离能力，以及可用于智能控制的时序预算余量。本文在部署三个并行网络切片的容器化open5GS平台上开展测量研究。我们设计并实现了一种命名空间感知的TC-BPF测量框架，解决了现有工具无法将时延观测归因到单个容器化网络功能的根本性障碍。在轻、中、重三种负载条件下，结合eMBB、URLLC和mMTC切片部署真实应用流量，共采集约2,800万组N3到N6匹配转发时延对。结果表明：eMBB转发时延对负载敏感，99百分位时延随负载增加从574微秒升至1,243微秒；URLLC时延对负载不敏感，验证了每UPF进程的隔离能力；mMTC表现TCP长尾行为。在本平台上，无论数据面负载如何，N4 PFCP会话修改时延始终保持在200微秒以下，表明在AI驱动UPF编排设计所假设的2毫秒预算内仍存在充裕的时序余量。测量框架、实验脚本及数据集结构已开源至：https://github.com/MP-Akhil-5G/open5gs-slice-measurement