Energy-Efficient Communication and Computing Scheduling in UAV-Aided Industrial IoT

Efficient data processing is crucial for industrial Internet of Things (IIoT) applications, but the limited energy and computing resources in IIoT devices (IIoT-Ds) pose constraints. This article utilizes a unmanned aerial vehicle (UAV) as a computing server for enhanced IIoT mission execution. Specifically, the energy consumption of IIoT-Ds and the UAV, as well as the weighted cost of the communication and computing scheduling strategy in the UAV-aided IIoT, are jointly taken into account. An optimization problem based on the system energy consumption is built under the constraints of UAV motion, computing offloading, and transmitting power allocation. A problem decoupling-based alternating optimization method is proposed to solve the minimization problem by decomposing it into three subproblems: 1) UAV motion optimization; 2) computing offloading configuration; and 3) transmitting power allocation. Through comparing the proposed communication and computing scheduling strategy with existing methods, simulation results illustrate its attainment of quasi-optimal performance, thereby validating the effectiveness of the alternating optimization method.