Abstract
In Industrial Internet application scenarios, due to the ubiquitous connection requirements of the massive Internet of Things (IoT) devices in the edge layer. The data transmission rate is reduced, and the transmission delay increases, increasing the transmission energy consumption per bit. So a low-energy transmission strategy based on real-time edge layer traffic sensing is proposed. First, a mixed-integer modeling method for low-energy transmission of the IoT is proposed. This method aims to optimize the overall energy consumption of the system. The low-energy transmission task of the IoT is modeled as a mixed-integer linear programming problem. Second, a traffic prediction method for the estimation of the number of access packets is designed. Solve the problem of fog access point (F-AP) state change caused by the real-time change of network load. Finally, an energy-driven mapping strategy is designed. The transmission task can be dynamically mapped to the appropriate F-AP. The simulation results show that the strategy proposed in this article can effectively reduce the transmission energy consumption of IoT devices and the overall energy consumption of the system in the massive device access scenario.
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