Construction and Application of Users′ Behavior Model in the Video on Demand System
By studying the behavior of Video-On-Demand users,a mathematical behavior model can be bulit,which may guide the improvement of the video data caching algorithms.This paper investigates the common mathematical models of the users′ behavior,analyzes a batch of video data and finds that the stretched exponential model can better match the real demanding frequencies of videos than the Zipf model.It also implement the stretched exponential model to model the playback length of videos and gets very good fitting,which confirms the correctness of the obtained playback length model.Moreover,it proposes a method to predict the upper bound of the hitting rate of video data caching algorithms based on the achieved video demanding frequency model and the playback length model.That upper bound plays an important role in quantitatively evaluating video data caching algorithms.