QoS-Aware Deployment and Synchronization of Digital Twins Over Federated Cloud Platforms for Smart Infrastructure Monitoring

This electronic increasingly, Digital Twin (DT) systems are being leveraged in smart infrastructure settings (e.g., structural health monitoring, intelligent traffic controls, and distributed utility networks). Yet, the available solutions all face hurdles that can prevent real-time synchronization of DT instances across federated cloud platforms, primarily due to latency variation, quality of service (QoS) assurance, and stale data, which are all consequences of heterogeneous computer environments. Most solutions depend on static cloud-only models of deployment, with no option for dynamic negotiation of resources. These provide long update times (typically greater than 200ms), low accuracy rates, and low real-time responsiveness. Additionally, traditional DT models were not developed with multi-regional deployment or QoS workloads in mind. In this work, a QoS-Aware Federated Digital Twin Orchestration Framework (Q-FDTO) is designed to allow latency-critical monitoring of infrastructure across different federated cloud regions, through the integration of a hybrid edge-cloud control plane, adaptive synchronization, jitter consideration for observed intervals, and dynamic resource allocation via reinforcement learning for defined QoS Service Level Objectives (SLOs). This system was evaluated on a smart city testbed of 1200 sensor nodes. The testbed monitored sensor readings for structural strain, vibration, and traffic density across twelve locations. The digital twin pipeline is comprehensive [i.e., (i) ingestion via Wi-Fi MQTT, (ii) stream fusion of all the sensor readings via Kalman filtering, and (iii) twin modeling of prediction, through a temporal graph convolutional network (T-GCN)]. To assess performance, sync policies were evaluated on metrics for average update latency (ms), sync drift (ms), and data consistency rate (%). The results demonstrate that Q-FDTO had an average update latency of 87.3 ms, reduced from 194.6 ms, and a 96.2% consistency rate across federated nodes with less than 2.5% sync drift over 10-minute intervals, showing Q-FDTO architecture ability for network boundaries and also compatible with AWS Outposts and Azure Arc hybrid cloud environments. It establishes a scalable and practical approach to latency-sensitive DT deployments in the realm of smart infrastructure systems.

@article{Narayana2025,
  title     = {QoS-Aware Deployment and Synchronization of Digital Twins Over Federated Cloud Platforms for Smart Infrastructure Monitoring},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {8},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {M V Narayana and Naveen Reddy N and Madhu S and Madhu T and Niladri Sekhar Dey and Sanjeev Shrivastava},
  doi       = {10.14569/IJACSA.2025.01608105},
  url       = {https://doi.org/10.14569/IJACSA.2025.01608105}
}