Content-aware distortion-fair video streaming in congested networks

Y. Li, Z. Li, M. Chiang, A. Robert Calderbank

Research output: Contribution to journalArticlepeer-review

52 Scopus citations


Internet is experiencing a substantial growth of video traffic. Given the limited network bandwidth resources, how to provide Internet users with good video playback quality-of-service (QoS) is a key problem. For video clips competing bandwidth, we propose an approach of Content-Aware distortion-Fair (CAF) video delivery scheme, which is aware of the characteristics of video frames and ensures max-min distortion-fair sharing among video flows. CAF leverages content-awareness to prioritize packet dropping during congestion. Different from bandwidth fair sharing, CAF targets end-to-end video playback quality fairness among users. The proposed CAF approach does not require rate-distortion modeling of the source, which is difficult to estimate. Instead, it exploits the temporal prediction structure of the video sequences along with a frame drop distortion metric to guide resource allocations and coordinations. Experimental results show that the proposed approach operates with limited overhead in computation and communication, and yields better QoS, especially when the network is congested.

Original languageEnglish (US)
Article number5235177
Pages (from-to)1182-1193
Number of pages12
JournalIEEE Transactions on Multimedia
Issue number6
StatePublished - Oct 2009

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Media Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


  • Fairness
  • Internet
  • Multimedia communication
  • Optimization
  • Rate distortion
  • Resource allocation
  • Video


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