Managing and Optimizing 5G & Beyond Network Resources for Multi-Task Digital Twin Applications in Industry 4.0

Ziran Min, Shuang Zhou, Zhuangwei Kang, Shashank Shekhar, C. Mahmoudi, A. Gokhale, A. Gokhale
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Abstract

Industry 4.0 is leading factories to undergo a significant transformation, where automation is achieved through the use of modern smart technologies, such as 5G & beyond $(5 \mathrm{G}+)$ network and digital twins. Yet, many Industrial Internet of Things (IIoT) applications, including smart factories and robotic repair, present challenges in delivering dedicated and real-time network services between the physical world entities and their digital twins due to the different network requirements of each sub tasks of the applications. Although 5G+ networks can provide high-speed, low-latency, and reliable network services, managing and optimizing the network resources in real-time remains complex and time-consuming. To address these challenges, this paper proposes solutions to manage and optimize $5 \mathrm{G}+$ network resources in real-time, and deliver dynamic and real time network requirements of multi-task digital twin applications.
管理和优化工业4.0中多任务数字孪生应用的5G及其他网络资源
工业4.0正在引领工厂进行重大转型,通过使用现代智能技术实现自动化,例如5G和超越(5 \ mathm {G}+)$网络和数字孪生。然而,许多工业物联网(IIoT)应用,包括智能工厂和机器人维修,由于应用程序的每个子任务的不同网络要求,在物理世界实体与其数字孪生之间提供专用和实时网络服务方面面临挑战。虽然5G+网络可以提供高速、低延迟、可靠的网络服务,但对网络资源的实时管理和优化仍然是复杂和耗时的。为了应对这些挑战,本文提出了实时管理和优化$5 \ mathm {G}+$网络资源的解决方案,并提供多任务数字孪生应用的动态和实时网络需求。
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