Digital Twin-Empowered Network Planning for Multi-Tier Computing

Conghao Zhou;Jie Gao;Mushu Li;Xuemin Sherman Shen;Weihua Zhuang
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引用次数: 10

Abstract

In this paper, we design a resource management scheme to support stateful applications, which will be prevalent in sixth generation (6G) networks. Different from stateless applications, stateful applications require context data while executing computing tasks from user terminals (UTs). Using a multi-tier computing paradigm with servers deployed at the core network, gateways, and base stations to support stateful applications, we aim to optimize long-term resource reservation by jointly minimizing the usage of computing, storage, and communication resources and the cost of reconfiguring resource reservation. The coupling among different resources and the impact of UT mobility create challenges in resource management. To address the challenges, we develop digital twin (DT) empowered network planning with two elements, i.e., multi-resource reservation and resource reservation reconfiguration. First, DTs are designed for collecting UT status data, based on which UTs are grouped according to their mobility patterns. Second, an algorithm is proposed to customize resource reservation for different groups to satisfy their different resource demands. Last, a Meta-learning-based approach is developed to reconfigure resource reservation for balancing the network resource usage and the reconfiguration cost. Simulation results demonstrate that the proposed DT-empowered network planning outperforms benchmark frameworks by using less resources and incurring lower reconfiguration costs.
多层计算的数字双授权网络规划
在本文中,我们设计了一种资源管理方案来支持有状态应用程序,这将在第六代(6G)网络中流行。与无状态应用程序不同,有状态应用程序在从用户终端(UT)执行计算任务时需要上下文数据。使用多层计算模式,在核心网络、网关和基站部署服务器以支持有状态应用程序,我们的目标是通过联合最小化计算、存储和通信资源的使用以及重新配置资源预留的成本来优化长期资源预留。不同资源之间的耦合和UT移动性的影响给资源管理带来了挑战。为了应对这些挑战,我们开发了具有两个元素的数字孪生(DT)网络规划,即多资源预留和资源预留重新配置。首先,DT被设计用于收集UT状态数据,在此基础上根据UT的移动性模式对UT进行分组。其次,提出了一种针对不同群体定制资源预留的算法,以满足他们不同的资源需求。最后,提出了一种基于元学习的方法来重新配置资源预留,以平衡网络资源使用和重新配置成本。仿真结果表明,所提出的DT授权网络规划通过使用更少的资源和更低的重新配置成本而优于基准框架。
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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