Adaptive Video Transmission Control System Based on Reinforcement Learning Approach Over Heterogeneous Networks

Video may pass through various types of heterogeneous networks during the process of transmission, which has adverse impacts on the real-time video quality. Traditional methods focus on how to compress videos based on the video flow without considering the real-time network information. This paper presents an adaptive method that combines video encoding and the video transmission control system over heterogeneous networks. This method includes the following steps: first, to collect and standardize the real-time information describing the network and the video, then to assess the video quality and calculate the video coding rate based on the standardized information, and then to process the encoded compression of the video according to the calculated coding rate and transfer the compressed video. The experiments show that there is a significant improvement for the quality of real-time videos transmission without changing the existing network, particularly the core equipment. Our solution is easy to deploy and implement quickly and may help to extensively ensure video quality for normal users.