Digital twin (DT) is the recurrent and common feature in discussions about future technologies, bringing together advanced communication, computation, and artificial intelligence, to name a few. In the context of Industry 4.0, industries such as manufacturing, automotive, and healthcare are rapidly adopting DT-based development. The main challenges to date have been the high demands on communication and computing resources, as well as privacy and security concerns, arising from the large volumes of data exchanges. To achieve low latency and high security services in the emerging DT, multi-tier computing has been proposed by combining edge/fog computing and cloud computing. Specifically, low latency data transmission, efficient resource allocation, and validated security strategies of multi-tier computing systems are used to solve the operational problems of the DT system. In this paper, we introduce the architecture and applications of DT using examples from manufacturing, the Internet-of-Vehicles and healthcare. At the same time, the architecture and technology of multi-tier computing systems are studied to support DT. This paper will provide valuable reference and guidance for the theory, algorithms, and applications in collaborative multi-tier computing and DT.

翻译：数字孪生是未来技术讨论中反复出现的共同特征，融合了先进通信、计算与人工智能等技术。在工业4.0背景下，制造、汽车、医疗等行业正迅速采用基于数字孪生的开发模式。迄今为止的主要挑战在于数据交换量大带来的通信与计算资源的高需求，以及隐私与安全问题。为实现新兴数字孪生中的低时延与高安全服务，研究者提出结合边缘/雾计算与云计算的多层级计算方案。具体而言，多层级计算系统的低时延数据传输、高效资源分配及已验证的安全策略被用于解决数字孪生系统的运行问题。本文通过制造业、车联网及医疗领域的实例介绍了数字孪生的架构与应用，同时研究了支撑数字孪生的多层级计算系统架构与技术。本文将为协同多层级计算与数字孪生的理论、算法及应用提供有价值的参考与指导。