Enhancing 5G Core with Multi-Access Edge Computing

Ho-Cheng Lee, F. Lin, Jyh-cheng Chen, Chien-Han Chen, Patrick Wang
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Abstract

This research employs NYCU-developed open source 5G core network $\boldsymbol{free5GC}$ and Intel open source edge computing platform OpenNESS to build a 5G private network. An online multi-person chorus application is then deployed on the edge platform to (1) achieve High Reliability and Low Latency Communication (URLLC) requirements, and (2) improve the backhaul bandwidth occupancy rate from the edge to the core network. In addition, this research implements the traffic influence function proposed in the 3GPP 5G standards, which can dynamically change traffic rules of the 5G core during execution, directing specific traffic to the edge applications in order to improve the performance of private networks. Finally, to verify the effectiveness of this schema, this research uses the example application deployed to compare the performance of the system equipped with edge computing with that without edge platform. Our analysis is done with both a physical RAN and the UERANSIM simulator.
用多接入边缘计算增强5G核心
本研究采用nyu自主研发的开源5G核心网$\boldsymbol{free5GC}$和Intel开源边缘计算平台open搭建5G专网。然后在边缘平台上部署在线多人合唱应用程序,以实现(1)高可靠性和低延迟通信(URLLC)要求;(2)提高从边缘到核心网的回程带宽占用率。此外,本研究实现了3GPP 5G标准中提出的流量影响功能,该功能可以在执行过程中动态改变5G核心的流量规则,将特定的流量引导到边缘应用,从而提高专网的性能。最后,为了验证该方案的有效性,本研究使用部署的示例应用程序比较了配备边缘计算的系统与未配备边缘平台的系统的性能。我们的分析是在物理RAN和UERANSIM模拟器上完成的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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