estion resulting from pre- vious transmissions. In [16] a congestion-distortion optimized (CoDiO) algorithm is proposed, which takes into account the effect of transmitted packets on delay. The scheme is intended to achieve an R-D performance similar to RaDiO streaming but specifically schedules packet CoDiO transmissions in a way that yields an optimal trade-off RaDiO between reconstruction distortion and congestion, mea- sured as average delay, on the bottleneck link. As with RaDiO, transmission actions are chosen at discrete transmission opportunities by finding an optimal policy over a time horizon. However, in CoDiO, the optimal policy minimizes the Lagrangian cost D + , where D is the expected distortion due to the policy A and A is the expected end-to-end delay, which measures congestion. End-To-End Delay (ms) CoDiO's channel model assumes a succession of high- bandwidth links shared by many users, followed by Figure 3.5-9 Performance comparison of RaDiO and CoDiO for video streaming over a bottleneck link. The horizontal axis shows a bottleneck last hop used only by the media stream the expected end-to-end delay due to the congestion caused by under consideration. CoDiO needs to know the capacity the video traffic. CoDiO causes much less congestion than RaDiO of the bottleneck, which can be estimated, for example, at the same PSNR. From [16]. Network adaptive media transport CHAPTER 3.5 deadlines for packets. Considerable gains are possible by accelerated retroactive decoding of packets, particularly if a multiple-deadline scheduler knows about this client capability and schedules accordingly. RaDiO typically assumes independent packet delays, but, in fact, Internet packet delays are highly dependent. In Section 3.5.5, an extension of RaDiO streaming that utilizes a Markov model of successive packet delays has been shown to CoDiO RaDiO rectify the poor performance that arises due to its simple iid channel model. Finally, we have considered self- congestion that might arise with streaming over a bot- tlene