Joint Optimization of Sensing and Communication for Digital Twin Edge Networks

Digital twin (DT) technology enables the replica of physical objects and environmental statuses of a physical system, which can be used for further simulation, analysis, and prediction. By combining DT with mobile edge computing (MEC), a new paradigm called digital twin edge networks (DITEN) is able to fill the gap between physical edge networks and digital systems and provide novel services to physical devices. Due to possible failure in data sensing, balancing sensing time and successful sensing rate needs to be considered to ensure the freshness of collected data in DITEN. Additionally, an optimal data scheduling policy is necessary to ensure efficient communication between physical devices and the edge server while maintaining the accuracy of DT. Therefore, this paper proposes a joint optimization problem for the sensing and communication for DITEN. Due to the nonconvex nature of the formulated problem, we decompose the original problem into three subproblems, and an iterative optimization algorithm is proposed to minimize the system overhead of DNT realization. The effectiveness of the proposed method is evaluated through extensive simulations.