论文标题

在数字二线6G网络中朝着经验驱动的交通管理和编排

Toward Experience-Driven Traffic Management and Orchestration in Digital-Twin-Enabled 6G Networks

论文作者

Tariq, Muhammad, Naeem, Faisal, Poor, H. Vincent

论文摘要

预期的6G网络有望支持极高的数据速率,低延迟和由机器学习授权的新应用。未来派的6G网络需要一个新颖的框架,该框架可用于操作,管理和优化其基本服务,例如超级可靠和低延迟的通信以及一切的互联网。近年来,人工智能(AI)在优化和设计网络方面取得了重大成功。启用AI的流量编排可以动态组织不同的网络架构和切片,以提供无线通信网络的动态性质的经验质量。 在本文中,我们提出了一个启用数字双胞胎的网络框架,该框架由AI授权,以满足设想6G网络的可变性和复杂性,以提供智能资源管理和智能服务提供。 Digital Twin铺平了一种通过创建6G网络的虚拟表示,及其相关的通信技术(例如,智能反射表面,Terahertz和Millimeter通信),计算系统(例如,云计算和FOG计算)及其相关的AlgorithM(例如,其相关的algorithm(例如,优化)(例如,优化和计算机))。然后,我们讨论并查看现有的AI支持的交通管理和编排技术,并强调6G网络中未来的研究方向和潜在解决方案。

The envisioned 6G networks are expected to support extremely high data rates, low-latency, and radically new applications empowered by machine learning. The futuristic 6G networks require a novel framework that can be used to operate, manage, and optimize its underlying services such as ultra-reliable and low-latency communication, and Internet of everything. In recent years, artificial intelligence (AI) has demonstrated significant success in optimizing and designing networks. The AI-enabled traffic orchestration can dynamically organize different network architectures and slices to provide quality of experience considering the dynamic nature of the wireless communication network. In this paper, we propose a digital twin enabled network framework, empowered by AI to cater the variability and complexity of envisioned 6G networks, to provide smart resource management and intelligent service provisioning. Digital twin paves a way for achieving optimizing 6G services by creating a virtual representation of the 6G network along with its associated communication technologies (e.g., intelligent reflecting surfaces, terahertz and millimeter communication), computing systems (e.g., cloud computing and fog computing) with its associated algorithms (e.g., optimization and machine learning). We then discuss and review the existing AI-enabled traffic management and orchestration techniques and highlight future research directions and potential solutions in 6G networks.

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