Performance Analysis of Digital Twin Communication under Different Deployment Configurations

Digital Twins rely on continuous data exchange with physical systems in order to maintain an accurate and timely representation of the real-world environment. Achieving low communication latency is therefore a critical requirement for many Digital Twin applications, particularly in IoT scenarios where near-real-time monitoring and control are required. While most research focuses on optimizing network infrastructures or deploying Digital Twin components closer to the edge, less attention has been given to the internal architecture of the Digital Twin middleware itself. In this paper we investigate the performance of the MQTT DataBridge component of the Eclipse BaSyx Asset Administration Shell (AAS) framework. In particular, the authors analyze the latency behavior under different deployment configurations, comparing a traditional mono-instance deployment with alternative multi-instance containerized configurations. The experiments evaluate latency across varying numbers of Digital Twin instances, message sizes, and CPU constraints. Results show that shared multi-instance deployments significantly reduce latency compared to the standard mono-instance configuration under moderate loads. However, the advantage diminishes as the number of instances increases beyond certain thresholds, revealing important scalability trade-offs. These findings highlight the impact of middleware deployment strategies on Digital Twin communication performance and provide guidelines for optimizing AAS-based Digital Twin infrastructures