一个基于值的扩展和分数接收控制的综合模型,以提高5G核心网络的资源利用效率
Ly Cuong Hoa1,2, Thanh Chuong Dang2, Viet Minh Nhat Vo3
1College of Information and Communication Technology, Can Tho University, Can Tho City, Vietnam.
PloS one
|August 18, 2025
概括
本研究介绍了TSUPF-FAC,这是一个用于优化5G网络中用户平面函数 (UPF) 实例的新机制. 它通过智能地管理UPF扩展和录取控制,有效地降低成本并提高资源利用率.
科学领域:
- 电信工程 电信工程 电信工程
- 计算机网络 计算机网络.
- 网络功能虚拟化 网络功能虚拟化
背景情况:
- 用户平面功能 (UPF) 在5G核心网络中至关重要,它将用户设备 (UE) 与数据网络 (DN) 连接起来.
- 高效的资源利用和降低成本是管理多个UPF实例的关键挑战.
- 现有的系统需要优化,以实现动态PDU会话管理.
研究的目的:
- 提出和评估一种用于优化UPF资源利用和降低运营成本的新机制.
- 通过智能UPF实例管理,提高5G核心网络的稳定性和性能.
- 开发一种方法,以有效地扩大UPF实例的规模和录取控制.
主要方法:
- 集成一个分数录取控制 (FAC) 机制与基于马尔科夫链的分析模型.
- 为UPF实例 (TSUPF-FAC) 开发基于值的扩展,并设置全球控制值.
- 在基于Kubernetes的Open5GS中实现基于值的缩放和分数录取控制 (TS-FAC) 算法.
主要成果:
- 开发的TSUPF-FAC机制证明了对UPF实例的有效优化.
- 模拟结果显示,分析模型和实验结果之间存在很强的一致性.
- 分析模型成功确定了性能提升的最佳录取门.
结论:
- 采用TSUPF-FAC方法可以显著提高资源利用率,并降低5G网络的成本.
- 分析建模和FAC的整合为UPF实例管理提供了一个强大的解决方案.
- 拟议的算法为动态的UPF资源分配提供了一个实用和有效的方法.
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