AI 中文总结
PRO-RAN框架在匹配硬件与流量条件下，分析O-RAN的CU、DU的处理器级特征，发现二者CPU时间差异，为其优化提供支撑。
AI 中文摘要
开放无线接入网（O-RAN）将无线接入网协议功能解耦，使集中单元（CU）和分布单元（DU）软件能在通用计算平台上运行。CU与DU的不同协议职责会产生不同的处理器工作负载和执行路径。传统性能指标（包括CPU利用率和吞吐量）仅能量化聚合资源使用情况，无法识别功能级执行成本或处理器微架构瓶颈；而处理器级表征则能为资源配置、功能部署、软件优化及硬件加速提供洞见。本文描述了一种受控表征框架，该框架在匹配的硬件和流量条件下评估独立部署的CU与DU功能。实验平台整合了Linux基金会OCUDU实现、仿真用户设备、基于ZeroMQ的无线接口及Open5GS核心。自动验证确认注册和双向分组传输正常后，对进程范围内的Intel VTune热点及自上而下微架构分析进行了分析。在流量负载下，300秒相同分析间隔内，CU的累计进程CPU时间从17.3秒增至37.4秒，DU则从462.0秒增至628.4秒。测量结果明确了CU与DU的不同执行特征，为功能特定的处理器分析与优化提供了依据。
英文摘要
Open Radio Access Network (O-RAN) disaggregates RAN protocol functions and enables Centralized Unit (CU) and Distributed Unit (DU) software to execute on general-purpose computing platforms. Different CU and DU protocol responsibilities produce different processor workloads and execution paths. Conventional performance metrics, including CPU utilization and throughput, quantify aggregate resource usage without identifying function-level execution costs or processor microarchitectural bottlenecks. Processor-level characterization, on the other hand, provides insights into resource provisioning, function placement, software optimization, and hardware acceleration. The paper describes a controlled characterization framework that evaluates independently deployed CU and DU functions under matched hardware and traffic conditions. The experimental platform integrates the Linux Foundation OCUDU implementation with an emulated User Equipment, a ZeroMQ-based radio interface, and an Open5GS core. Automated validation confirms registration and bidirectional packet delivery before process-scoped Intel VTune Hotspots and Top-Down Microarchitecture Analysis. Under traffic load, accumulated process CPU time increases from 17.3 s to 37.4 s for the CU and from 462.0 s to 628.4 s for the DU during equal 300-s profiling intervals. The measurements identify distinct CU and DU execution characteristics and motivate function-specific processor analysis and optimization.
Comments7 pages, 6 figures
