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
Crossover scaling effects in aggregated TCP traffic with congestion losses
ACM SIGCOMM Computer Communication Review
A wavelet-based framework for proactive detection of network misconfigurations
Proceedings of the ACM SIGCOMM workshop on Network troubleshooting: research, theory and operations practice meet malfunctioning reality
A counterexample in congestion control of wireless networks
MSWiM '05 Proceedings of the 8th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems
On TCP and self-similar traffic
Performance Evaluation - Long range dependence and heavy tail distributions
A counterexample in congestion control of wireless networks
Performance Evaluation
A new methodology for TCP evaluation in a multiuser web environment
Computer Communications
Investigating self-similarity and heavy-tailed distributions on a large-scale experimental facility
IEEE/ACM Transactions on Networking (TON)
Multiservice IP network qos parameters estimation in presence of self-similar traffic
NEW2AN'06 Proceedings of the 6th international conference on Next Generation Teletraffic and Wired/Wireless Advanced Networking
TCP's role in the propagation of self-similarity in the Internet
Computer Communications
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Abstract: Long-range dependence has been observed in many recent Internet traffic measurements. In addition, some recent studies have shown that under certain network conditions, TCP itself can produce traffic that exhibits dependence over limited timescales, even in the absence of higher-level variability. In this paper, we use a simple Markovian model to argue that when the loss rate is relatively high, TCP's adaptive congestion control mechanism indeed generates traffic with OFF periods exhibiting power-law shape over several timescales and thus introduces pseudo-long-range dependence into the overall traffic. Moreover, 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. We can thus explain why a single TCP connection can produce a time-series that can be misidentified as self-similar using standard tests.