Providing predictable streaming performance in mobile video streaming

Much work has been done to improve the performance of video streaming over mobile data networks. The widespread adoption of HTTP/TCP for video streaming further complicates the problem as TCP´s own dynamics add even more fluctuations to the already unpredictable network bandwidth. Not surprisingly, none of the existing video bit-rate selection algorithms can achieve consistent or predictable streaming performance in the presence of wide network bandwidth fluctuations. This work tackles this problem by developing a new model to capture the statistical correlations between streaming performance, video bit-rate selection, and past TCP throughput data. Based on a novel post-streaming rate analysis technique, the proposed model can be used to predict the streaming performance of future video sessions at any given video bit-rate choices. This not only enables content providers to control the quality-of-service for streaming users, but also to ensure consistent streaming performance for users with widely different access bandwidths.