In this paper, the problem of low-latency communication and computation resource allocation for digital twin (DT) over wireless networks is investigated. In the considered model, multiple physical devices in the physical network (PN) needs to frequently offload the computation task related data to the digital network twin (DNT), which is generated and controlled by the central server. Due to limited energy budget of the physical devices, both computation accuracy and wireless transmission power must be considered during the DT procedure. This joint communication and computation problem is formulated as an optimization problem whose goal is to minimize the overall transmission delay of the system under total PN energy and DNT model accuracy constraints. To solve this problem, an alternating algorithm with iteratively solving device scheduling, power control, and data offloading subproblems. For the device scheduling subproblem, the optimal solution is obtained in closed form through the dual method. For the special case with one physical device, the optimal number of transmission times is reveled. Based on the theoretical findings, the original problem is transformed into a simplified problem and the optimal device scheduling can be found. Numerical results verify that the proposed algorithm can reduce the transmission delay of the system by up to 51.2\% compared to the conventional schemes.

翻译：本文研究了无线网络中面向数字孪生（DT）的低延迟通信与计算资源分配问题。在所考虑的模型中，物理网络（PN）中的多个物理设备需要频繁地将与计算任务相关的数据卸载至由中央服务器生成和控制的数字网络孪生（DNT）。由于物理设备的能量预算有限，在数字孪生过程中必须同时考虑计算精度和无线传输功率。该联合通信与计算问题被建模为一个优化问题，目标是在满足总PN能量和DNT模型精度约束的条件下最小化系统的整体传输延迟。为求解该问题，提出了一种交替算法，该算法通过迭代求解设备调度、功率控制和数据卸载子问题。对于设备调度子问题，通过对偶方法获得了闭式最优解。针对单物理设备的特殊情形，揭示了最优传输次数的规律。基于上述理论发现，原问题被转化为一个简化问题，并得以确定最优设备调度方案。数值结果验证了所提算法相比传统方案可将系统传输延迟降低高达51.2%。