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Abstract:

Abstract – This paper presents a trace-driven simulation study of three classes of retransmission timeout (RTO) estimators in the context of low-bitrate real-time streaming over the Internet. We explore the viability of employing retransmission timeouts in NACK-based real-time streaming applications that support multiple retransmission attempts per lost packet. In such applications, real-time RTO estimation plays a major role (i.e., poor RTO estimation results in a larger number of duplicate packets and sometimes more frequent underflow events). Our study is based on trace data collected during a number of real-time streaming tests conducted between our dialup clients in all 50 states of the U.S. (including 653 major U.S. cities) and our backbone video server during a seven-month period. First, we define a generic performance measure for assessing the quality of hypothetical RTO estimators based on the samples of the roundtrip delay (RTT) recorded in the trace data. Second, using this performance measure, we evaluate the class of TCP-like estimators, find the most optimal estimator given our performance measure, and establish power laws that describe the tradeoff between the optimal number of duplicate packets and the optimal timeout waiting time. Third, we introduce a new class of RTO estimators based on delay jitter and show that they perform significantly better than TCP-like estimators in NACKbased applications. Finally, we gain a major insight into the RTT process by establishing which tuning parameters of an RTO estimator make it optimal given our performance measure and our experimental data, and give our explanation of the observed phenomena. I.

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