A User Behaviour-Based Video Segmentation Strategy for High-Concurrency Environment

With the development of the media industry, maximizing concurrency while ensuring the user’s viewing experience has become an important research topic for each major video website. Currently, one solution is to slice the video, which conserves server bandwidth. Therefore, the design of segment durations has been widely discussed in academia. The research shows that the longer the segment duration is, the better the user experience; however, the increase in video segment duration has a negative impact on the concurrency of the video website. In this paper, a variable length segmentation strategy based on user behaviour is proposed for video segmentation. In the early stage of video browsing, the video loading is ensured, and a short video segmentation strategy is adopted. When the number of users becomes stable, the segment duration is slowly increased to a fixed value to ensure fluency for the users watching the videos. In this paper, the JMeter test tool is used to test the concurrency volume. Through experimental verification, the variable length video segmentation algorithm proposed in this paper is shown to effectively improve the concurrency of the video websites.