Distortion Optimized Packet Scheduling and Prioritization of Multiple Video Streams over 802.11e Networks

Politis, Ilias; Tsagkaropoulos, Michail; Pliakas, Thomas; Dagiuklas, Tasos

doi:https://doi.org/10.1155/2007/76846

Advances in Multimedia

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Multimedia Transmission over Emerging Wireless Technologies

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Research Article | Open Access

Volume 2007 | Article ID 076846 | https://doi.org/10.1155/2007/76846

Distortion Optimized Packet Scheduling and Prioritization of Multiple Video Streams over 802.11e Networks

Ilias Politis,¹Michail Tsagkaropoulos,²Thomas Pliakas,³and Tasos Dagiuklas⁴

Academic Editor: Stavros Kotsopoulos

Received11 Jun 2007

Accepted20 Aug 2007

Published16 Oct 2007

Abstract

This paper presents a generic framework solution for minimizing video distortion of all multiple video streams transmitted over 802.11e wireless networks, including intelligent packet scheduling and channel access differentiation mechanisms. A distortion prediction model designed to capture the multireferenced frame coding characteristic of H.264/AVC encoded videos is used to predetermine the distortion importance of each video packet in all streams. Two intelligent scheduling algorithms are proposed: the “even-loss distribution,” where each video sender is experiencing the same loss and the “greedy-loss distribution” packet scheduling, where selected packets are dropped over all streams, ensuring that the most significant video stream in terms of picture context and quality characteristics will experience minimum losses. The proposed model has been verified with actual distortion measurements and has been found more accurate than the “additive distortion” model that omits the correlation among lost frames. The paper includes analytical and simulation results from the comparison of both schemes and from their comparison to the simplified additive model, for different video sequences and channel conditions.

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Copyright

Copyright © 2007 Ilias Politis et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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