Time-Sensitive Networking-Driven Deterministic Low-Latency Communication for Real-Time Telemedicine and e-Health Services

Abstract

With the convergence of telemedicine and electronic health (e-health) services, Consumer Internet of Things (CIoT) enabled smart healthcare has attracted much attention from researchers. Telemedicine and e-health care can help to eliminate geographical barriers and provide high-quality medicine services. Whereas, deterministic low-latency communication is a major problem in smart healthcare system with commercial network, since the latency can affect the process of diagnosis and treatment while producing inaccuracy. To address this issue, Time Sensitive Networking (TSN) is introduced in this article for bounded lowlatency network services. First, we present a Digital Twin based TSN (DTTSN) framework where digital modeling and intelligent simulation are performed under a virtual environment. Second, a digital twin scheduling model is created to predict the forwarding delay. In order to enhance model adaption in different scenarios, cycle generative adversarial network (CycleGAN) is adopted to train the scheduling model. Finally, the optimal routing strategy deduced in digital twin network is fed back to physical network for automated configuration. Simulation results verify that our digital twin network can promote visibility of operations and predictions of physical network scheduling and routing, while optimizing delay and balancing link load.