Synchronization is fundamental for mirroring real-world entities in real-time and supporting effective operations of Digital Twins (DTs). Such synchronization is enabled by the communication between the physical and virtual realms, and it is mostly assumed to occur in real-time. However, this is not the case, as real-life scenarios witness performance degradation that may lead to synchronization problems. Hence, as such a problem has yet to be thoroughly analyzed in the literature, this work attempts to uncover potential challenges by emulating and analyzing the DT traffic flows in networks of different scales, for different communication protocols, and with various flow configurations. We propose a Twin Alignment Ratio metric to evaluate the synchronization performance to achieve this goal. Consequently, the findings reveal the interplay of network infrastructure, protocol selection, and twinning rate on synchronization and performance.

Digital Twins (DTs) are becoming integral in sectors such as energy and manufacturing, catalyzing applications from monitoring and analysis to optimization and autonomous management. However, data in different formats, volumes, and qualities require high processing capabilities for integration. Moreover, the functionalities in DT must work together, bringing interoperability challenges that have necessitated extensive manual programming. To address these, we propose Internet of Twins, a disaggregated DT deployed in distributed cloud architecture where interconnections are made using a remote procedure call framework, gRPC. Using this, we develop the Digital Twin as a Platform with Knowledge Graph-based Orchestration. Here, we implement a recursive execution algorithm to ensure necessary data is processed in the correct sequence autonomously. Then, we implement a wind energy pilot application and evaluate the performance. The results show that our approach lowers data preprocessing and line-of-code overhead up to 20% and 26%, creating a flexible and scalable architecture.