Abstract
Abstract In the rapid development of industrial networks, in the face of complex and changeable network environments, the demand for reliable and efficient communication systems is becoming increasingly prominent. In this paper, a PRP protocol optimization method based on Q-learning under the Linux operating system is proposed. By introducing a Q-learning algorithm, the adaptive learning of a dynamic network environment is realized through Q-value update rules, to adjust PRP protocol parameters. The experimental results show that the optimization of PRP protocol based on Q-learning can improve the performance of PRP protocol under various network conditions and load changes, thus improving communication reliability.
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