Abstract
According to the data characteristics in the power Internet of Things (IoT), this paper proposed a dynamic performance adjustment algorithm based on the negative feedback mechanism of the power Internet of Things. In order to realize dynamic performance adjustment in the power Internet of Things, the algorithm predicts the number of messages written to the message queue through the time series prediction model, and dynamically adjusts the number of threads processed by the task module. First, the autoregressive integrated moving average (ARIMA) model is used to predict the number of messages written to the message queue. Then, the optimal number of threads is dynamically calculated from the predicted number of messages and the processing power of a single thread. Finally, it is verified by the data written to the message queue when the IoT management platform is running normally and when the platform is just implementation. The experimental results show that the dynamic performance adjustment algorithm based on the negative feedback mechanism of the power Internet of Things can greatly reduce the accumulation of messages and improve the operating efficiency of the system.
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