An Adaptive Media-Aware Retransmission Timeout Estimation Method for Low-Delay Packet Video

Time-constrained error recovery is an integral component of reliable low-delay video applications. Regardless of the error-control method adopted by the application, unacknowledged or missing packets must be quickly identified as lost or delayed, so that necessary actions can be taken by the server/client on time. Historically, this problem has been referred to as retransmission timeout (RTO) estimation. Earlier studies show that existing RTO estimators suffer from either long loss detection times or a large number of spurious timeouts. The goal of this study is to address these problems by developing an RTO estimation method specifically tailored for low-delay video applications. In the media-unaware mode, this method exploits the temporal dependence in packet delay to optimally manage the tradeoff between the amount of overwaiting and redundant retransmission rate. As opposed to existing methods, our approach is completely adaptive to the source video characteristics and time-varying network conditions, and does not use any preset parameters. In the media-aware mode, on the other hand, the timeout estimates are jointly optimized based on the importance and urgency of the video packets such that the rendering quality is maximized under the given rate constraints. With a comprehensive set of simulation and experimental results, we show that both the media-unaware and media-aware RTO estimators detect lost packets faster and more accurately than their rivals. Furthermore, our results also substantiate the fact that the media-aware RTO estimator outperforms all other RTO estimators in terms of video quality