Enabling Parallel Streaming of Multiple Video Sections by Segment Scheduling

ABSTRACT

A type of application that occupies most of the Internet is online multimedia, which is usually referred to online video or video streaming with providers such as Youtube, Netflix and Hulu. With the advancement in the Internet technology, people can watch an entire 2-hours long movie. However, people sometimes want to skip to different sections of a video to see whether the whole video is of their interest. Doing so usually requires the video to restart buffering and causes delay. To alleviate this issue, this research proposes a parallel streaming method based on the modification of the Dynamic Adaptive Streaming over HTTP (DASH) technique. By splitting video into smaller segments and modifying the segment scheduling, we can stream a video at many different positions in parallel so that users can jump to the different sections with minimal delay. The performance evaluation of the proposed technique shows that such streaming is possible through video segment scheduling with higher throughput in exchange for higher bandwidth requirement and utilization.

References

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Index Terms

• Applied computing

  • Document management and text processing

    • Document capture

      • Graphics recognition and interpretation

• Computing methodologies

  • Computer graphics

• Theory of computation

  • Design and analysis of algorithms

    • Approximation algorithms analysis

      • Scheduling algorithms

    • Online algorithms

      • Online learning algorithms

        • Scheduling algorithms

  • Theory and algorithms for application domains

    • Machine learning theory

      • Reinforcement learning

        • Sequential decision making