ventional feedback scheme in which each packet is acknowledged With rich acknowledgments, the client does not ac- individually upon receipt, there are only two possible knowledge each data unit separately. Instead, it periodi- observations, ACK and . Regardless of the scheme, the cally transmits a packet that positively acknowledges all optimization algorithm calculates the probabilities of packets that have arrived SO far and negatively acknowl- each path through the tree given a policy and then edges (NACK) packets that have not yet arrived. A rich chooses the policy that yields the best trade-off between acknowledgment packet hence provides a snapshot of the expected number of transmissions p() and loss proba- state of the receiver buffer. bility E(TII). Rich acknowledgments require some changes to the Figure 3.5-6 compares average PSNR versus trans- basic RaDiO framework described in Section 3.5.2. As mitted bit rate for the 13-s Foreman sequence streamed shown in [6], a transmission policy TT for a data unit can using the rich feedback scheme and using the conven- be understood in terms of a Markov decision process. At tional acknowledgment scheme. Two-layer SNR-scalable discrete times ti the server makes an observation Oi and H.263+ is used for the encoding [9]. The bit rate of the then takes a transmission action ai specifying send or base layer alone is 32 kbps with an average PSNR of 27 don't send. Sequences of observation and action pairs (0i, dB. When the enhancement layer is added, the encoded ai) in time can be enumerated in a Markov decision tree. rate becomes 69 kbps with an average PSNR of 30.5 dB. Each node qi in the tree specifies a particular history of The results are for simulation experiments with a 10% observations and actions (ao, 00), (a1, 01), (ai, oi). loss rate for both media packets and feedback packets. NAK(t,) NAK(t) NAK(t NAK(1 don't send don't send NAK(t,) NAK(t) initial don't send state NAK(t) NAK(t) don't send NAK(t NAK(t,) don't send NAK(tN) t-N-1 Figure 3.5-5 State space for t