Corrections to "How Does TCP Generate Pseudo-Self-Similarity?"
ACM SIGCOMM Computer Communication Review
On the autocorrelation structure of TCP traffic
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Advances in modeling and engineering of Longe-Range dependent traffic
On the autocorrelation structure of TCP traffic
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Advances in modeling and engineering of Longe-Range dependent traffic
The End-to-End Performance Effects of Parallel TCP Sockets on a Lossy Wide-Area Network
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
On the Contribution of TCP to the Self-Similarity of Network Traffic
IWDC '01 Proceedings of the Thyrrhenian International Workshop on Digital Communications: Evolutionary Trends of the Internet
SpringSim '07 Proceedings of the 2007 spring simulaiton multiconference - Volume 1
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Abstract Long-range dependence has been observed in many recent Internet traffic measurements. Previous studies have shown that there is a close relationship between heavy-tailed distribution of various traffic parameters and the long-range dependent property. In this paper, we use a simple Markov chain model to argue that when the loss rate is relatively high, TCP''s adaptive congestion control mechanism indeed generates traffic with heavy-tailed OFF, or idle, periods, and therefore introduces long-range dependence into the overall traffic. Moreover, the degree of such long-range dependence, measured by the Hurst parameter, increases as the loss rate increases, agreeing with many previous measurement-based studies. In addition, we observe that more variable initial retransmission timeout values for different packets introduces more variable packet inter-arrival times, which increases the burstiness of the overall traffic. Finally, we show that high loss conditions can lead to a heavy-tailed distribution of transmission times even for constant-sized files. This means that file size variability need not be the only cause of heavy-tailed variability in transmission durations.