We introduce an Internet packet delay and loss model for use in rate-distortion optimized media streaming. Our scheme uses feedback to learn the delay over the channel in the recent past and then finds probability mass functions for delays at later times by using chains of approximated conditional delay distributions. With an Internet delay trace we have collected and a performance metric that we introduce, we show that our scheme is far more accurate than the commonly-used model, which assumes packet delays to be i.i.d. Γ-distributed, at predicting arrival outcomes for groups of successively-transmitted Internet packets. In addition, we outline our Linux-based one-way delay trace collection techniques and we show the suitability of the shifted Γ distribution for modeling conditional packet delays over Internet links that include a cable modem last hop.
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