论文标题

Metaverse中的双向数字双胞胎和边缘计算

Bi-directional Digital Twin and Edge Computing in the Metaverse

论文作者

Yu, Jiadong, Alhilal, Ahmad, Hui, Pan, Tsang, Danny H. K.

论文摘要

元评估已经出现了,将我们的生活方式扩展到身体局限性之外。作为元评估中的基本组成部分,数字双胞胎(DTS)是物理项目的实时数字复制品。多访问边缘计算(MEC)为最终用户提供响应式服务,以确保身临其境且交互式的元元体验。尽管物理对象,最终用户和边缘计算系统的数字表示(DT)在元评估中至关重要,但这些DTS的构建以及它们之间的相互作用尚未得到很好的评价。在本文中,我们讨论了DT和MEC系统之间的双向依赖,并研究了MEC服务器上对象和用户的DT的创建以及DT辅助边缘计算(DTEC)。为了确保MEC服务器之间的无缝切换并避免间歇性的荟萃分析服务,我们还探索了本地MEC服务器上本地DTEC与云服务器上的全局DTEC之间的相互作用,这是由于网络状态的动态性质(例如,通道状态和用户的Mobility)。我们通过案例研究研究了本地DTEC中资源分配策略的持续学习框架。我们的策略减轻了物理数字双胞胎之间的不同步,确保了更高的学习成果,并提供了令人满意的元体验。

The Metaverse has emerged to extend our lifestyle beyond physical limitations. As essential components in the Metaverse, digital twins (DTs) are the real-time digital replicas of physical items. Multi-access edge computing (MEC) provides responsive services to the end users, ensuring an immersive and interactive Metaverse experience. While the digital representation (DT) of physical objects, end users, and edge computing systems is crucial in the Metaverse, the construction of these DTs and the interplay between them have not been well-investigated. In this paper, we discuss the bidirectional reliance between the DT and the MEC system and investigate the creation of DTs of objects and users on the MEC servers and DT-assisted edge computing (DTEC). To ensure seamless handover among MEC servers and to avoid intermittent Metaverse services, we also explore the interaction between local DTECs on local MEC servers and the global DTEC on the cloud server due to the dynamic nature of network states (e.g., channel state and users' mobility). We investigate a continual learning framework for resource allocation strategy in local DTEC through a case study. Our strategy mitigates the desynchronization between physical-digital twins, ensures higher learning outcomes, and provides a satisfactory Metaverse experience.

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