Self-adaptive process optimisation method for SBS cloud application based on reinforcement learning Online publication date: Mon, 21-Dec-2020
by Haiyan Hu; Chang Su
International Journal of Information and Communication Technology (IJICT), Vol. 18, No. 1, 2021
Abstract: To solve the problem of poor comprehensive performance of the traditional SBS cloud application adaptive process optimisation method, a new SBS cloud application adaptive process optimisation method based on reinforcement learning was proposed. Establish the adaptive action type selection model, realise the optimal choice of operation type, build the cloud application adaptive process optimisation model for resource cost, convert the problem into the corresponding mathematical model, solve and make the mathematical model of the algorithm, and obtain the best adaptive process optimisation scheme SBS cloud application. The simulation results show that the predicted load value of the method is the closest to the actual load value, the relative error of the prediction is less than 21.03, and the average time is less than 2.3 s, indicating that the method has good performance and high practical application value.
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