ODTE: A Metric for Digital Twin Entanglement

Digital Twins (DTs) have recently emerged as a valuable approach for modeling, monitoring, and controlling physical objects in Industrial Internet of Things applications. Measuring the quality of entanglement between the digital and physical counterparts plays a crucial role in the adoption of DTs. In this context, entanglement denotes how well a DT mirrors its counterpart and the extent to which the behavior of the physical counterpart aligns with the commands issued by the DT. In this paper we propose a concise yet expressive and original metric for representing the quality of entanglement, namely Overall Digital Twin Entanglement (ODTE), based on two key factors: timeliness and completeness, i.e., the freshness of the collected data and the ratio between collected and total data, respectively. In addition, the paper describes how we have built our industrial testbed implemented on top of Kubernetes, where we show practical applications of the proposed ODTE metric by highlighting and discussing its benefits in realistic use cases.