Performance Optimization for Digital Internet-of-Things Twins Over Wireless Networks

In this article, the problem that minimizes the control error for digital Internet-of-Things (IoT) twins over realistic wireless networks is investigated. In the considered system, devices in the physical IoT system transmit real-time status information to a base station (BS) and the digital IoT twin is built with the information. Based on the digital IoT twin, the BS will send control messages to physical devices so as to control devices to reach the target status. Since the status information of the distributed devices is transmitted over wireless channels, the wireless factors have an effect on the control performance, such as the limited wireless bandwidth and packet errors. Therefore, the BS requires to select an appropriate subset of devices and control the transmit power of devices to reduce the probability of packet errors so as to improve the control accuracy. This device selection and power allocation problem is formulated as a mixed integer nonlinear programming (MINLP) problem whose goal is to minimize the control error between the real status and the target status of devices. To obtain the solution to this problem, this paper proposes a joint device selection and power allocation (JDSPA) algorithm to decouple the original optimization problem into subproblems which are solved alternatively. Simulation results show that the proposed algorithm can reduce the control error by 12.49% and 40.13% respectively, compared to: a) an optimal device selection algorithm with a fixed transmit power, and b) an optimal power allocation algorithm with random device selection.