Supporting applications in emerging domains like cyber-physical systems and human-in-the-loop scenarios typically requires adherence to strict end-to-end delay guarantees. Contributions of many tandem processes unfolding layer by layer within the wireless network result in violations of delay constraints, thereby severely degrading application performance. Meeting the application's stringent requirements necessitates coordinated optimization of the end-to-end delay by fine-tuning all contributing processes. To achieve this task, we designed and implemented EDAF, a framework to decompose packets' end-to-end delays and determine each component's significance for 5G network. We showcase EDAF on OpenAirInterface 5G uplink, modified to report timestamps across the data plane. By applying the obtained insights, we optimized end-to-end uplink delay by eliminating segmentation and frame-alignment delays, decreasing average delay from 12ms to 4ms.

翻译：支持信息物理系统与人机协同等新兴领域的应用，通常需要遵循严格的端到端时延保证。无线网络中层层展开的多个串联过程的贡献会导致时延约束被违反，从而严重降低应用性能。满足应用的严苛要求需要调整所有贡献过程以协同优化端到端时延。为实现此目标，我们设计并实现了EDAF——一种用于分解数据包端到端时延并确定5G网络中每个组成部分重要程度的框架。我们在OpenAirInterface 5G上行链路中展示了EDAF，该链路经过修改以报告数据平面各节点的时间戳。通过应用获得的洞察，我们消除了分段和帧对齐时延，将端到端上行时延从12ms优化至4ms。