End-to-end Stochastic Scheduling of Scalable Video Over Time Varying Channels

Nesrine Changuel (1) , Nicholas Mastronarde (2) , Mihaela van Der Schaar (2) , Bessem Sayadi (1) , Michel Kieffer (3, 4)

1 Alcatel Lucent Bell Labs
2 UCLA - University of California [Los Angeles]
3 L2S - Laboratoire des signaux et systèmes
4 LTCI - Laboratoire Traitement et Communication de l'Information

This paper addresses the problem of video on demand delivery over a time-varying wireless channel. Packet scheduling and buffer management are jointly considered for scalable video transmission to adapt to the changing channel conditions. A proxy-based filtering algorithm among scalable layers is considered to maximize the decoded video quality at the receiver side while keeping a minimum playback margin. This problem is cast in the context of Markov Decision Processes which allows the design of foresighted policies maximizing some long-term reward. Experimental results illustrate the benefit of this approach compared to a shortterm policy in term of average PSNR improvement.

Domaines: Traitement du signal et de l'image [eess.SP]; Réseaux et télécommunications [cs.NI]; Traitement du signal et de l'image [eess.SP]

Nesrine Changuel, Nicholas Mastronarde, Mihaela van Der Schaar, Bessem Sayadi, Michel Kieffer. End-to-end Stochastic Scheduling of Scalable Video Over Time Varying Channels. MM'10: International conference on Multimedia, Oct 2010, Florence, Italy. pp.731-734, ⟨10.1145/1873951.1874064⟩. ⟨hal-00549244⟩