Real-time smoothing for network adaptive video streaming

  • Authors:

  • Kui Gao;Wen Gao;Simin He;Yuan Zhang

  • Affiliations:

  • Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China and Graduate School, Chinese Academy of Sciences, Beijing 100039, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China and Graduate School, Chinese Academy of Sciences, Beijing 100039, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China;Graduate School, Chinese Academy of Sciences, Beijing 100039, China and Beijing Broadcasting Institute, Beijing 100024, China

  • Venue:
  • Journal of Visual Communication and Image Representation
  • Year:
  • 2005

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Abstract

Real-time streaming delivery over the Internet with bandwidth variation is a very challenging task. It is important to smooth the quality variability and improve the utilization of the available network bandwidth. In this paper, we propose a real-time optimal smoothing scheduling algorithm for network adaptive video streaming with the variable network bandwidth and packet loss. The algorithm adopts a rate-distortion optimized framework and real-time scheduling scheme to select and schedule the packets according to the network status. It attempts to minimize the quality variability at the client end while at the same time maximizing the utilization of the variable network bandwidth. Experiments show that, compared with frame-based scheduling algorithm, our proposed real-time smoothing algorithm improves and smoothes the quality in decoded video frames.