Digital Twin (DT) has become a game-changing technology in many AI/ML-driven distributed computing applications leveraging next-generation mobile wireless networks, e.g., 6G, by fully replicating the physical devices and produce real-time interactions to efficiently manage the entire system. DT in multi-tier distributed computing systems enables communication-oriented computing from the cloud-computing-based twin object to the edge-based twin objects by distributing storage/caching, control, and networking capabilities, thus extending the traditional cloud computing architecture to the edge of the network. The new computing model resulting from combining computer-communications and multi-dimensional resources management with multi-tier distributed computing will promote the rapid development of DT and enable efficient task offloading of computation-intensive tasks, so as to realize ultra-reliable and low latency of the interactions between physical and virtual objects. However, attaining the full potential of DT in practical multi-tier distributed computing scenarios is challenging, and there are still many important open research problems, especially from the various perspectives of distributed computing. This workshop aims to provide a forum for the latest advances for DT-enabled 6G multi-tier distributed computing research, innovations, and applications to the distributed computing communities, in order to bridge the gap between theory and applications. We solicit high-quality original research papers on the topics which include, but are not limited to:

·         Fundamental limits and performance analysis of resource allocation for DT-enabled 6G multi-tier distributed computing

·         Machine learning aided DT in 6G multi-tier distributed computing

·         Joint optimal design of signal processing, computing, communications for DT-enabled 6G multi-tier distributed computing

·         Security and privacy issues of DT-enabled 6G multi-tier distributed computing

·         Testbeds for DT-enabled 6G multi-tier distributed computing

·         Federated learning for DT in multi-tier distributed computing systems

·         Over-the-air computation for DT in multi-tier distributed computing systems

·         Twin models and optimization in multi-tier distributed computing systems