A new framework for MPEG video delivery over heterogeneous networks

  • Authors:
  • Chih-Heng Ke;Naveen Chilamkurti

  • Affiliations:
  • Department of Computer Science and Information Engineering, No. 1, University Road, Jinning, Kinmen 892, Taiwan, ROC;Department of Computer Science and Computer Engineering, La Trobe University, Bundoora, Victoria 3086, Australia

  • Venue:
  • Computer Communications
  • Year:
  • 2008

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Abstract

The failure of legacy packet markers, such as the Single Rate Three Color Marker (SRTCM) and the Two Rate Three Color Marker (TRTCM), to protect important data from being dropped, renders a poor delivery of video quality over Differentiated Services (DiffServ) networks due to the hierarchical structure of MPEG video. Therefore, we propose a content-aware packet marking scheme, which we call Two Markers System (TMS), to improve the delivery quality of MPEG video streams. TMS places marker modules at both the video source and the edge of a DiffServ network. The source marking modules act at the application-level to set an importance indicator in the IP header of the MPEG frame packet by evaluating the contribution of the packet to the expected picture quality perceived by an end user. Meanwhile, at the edge of the DiffServ network, the Enhanced Token Bucket Three Color Marker (ETBTCM) is proposed to perform packet marking at the network-level in accordance with the pre-assigned importance of individual video frame packets. When the traffic flow is measured as out-of-profile, the less important packets will be marked with higher probability than the more important ones. Therefore, in the event of network congestion, less important frame packets can be dropped before more important ones. Consequently, a better delivered video quality can be provided. Further, due to the convenience offered by wireless networks, more users choose mobile devices to connect to the Internet. Therefore, a Video Differentiator is suggested, placed at the entry to the IEEE 802.11e wireless network, to provide traffic differentiation and better service for video traffic. We use authentic MPEG4 video traffic traces to evaluate this framework. Results show that better video quality can be delivered over our proposed new framework.