An adaptive-predictive architecture for video streaming servers

  • Authors:
  • Stenio Fernandes;Judith Kelner;Djamel Sadok

  • Affiliations:
  • Center of Informatics (CIn), Federal University of Pernambuco (UFPE), Recife, PE, Brazil;Center of Informatics (CIn), Federal University of Pernambuco (UFPE), Recife, PE, Brazil;Center of Informatics (CIn), Federal University of Pernambuco (UFPE), Recife, PE, Brazil

  • Venue:
  • Journal of Network and Computer Applications
  • Year:
  • 2011

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Abstract

Providing perceptually good quality video streaming over today's Internet is a complex task, as the available bandwidth and the encoded video rate can exhibit significant variability at different time scales. This research investigates the ways that such mismatches can be addressed, suggesting that this can be done by minimizing quality variability and increasing the overall video quality rendered to end-systems. Towards this end, we formulate a combination of innovative congestion control-aware mechanisms and filtering techniques. Our proposal involves extracting explicit information from the network, as well as providing the video source with consistent and stable information. We investigate this proposal throughout the following pages and reveal its efficiency by simulating representative scenarios.