A stochastic model of TCP/IP with stationary random losses
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
The failure of TCP in high-performance computational grids
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
A non-instrusive, wavelet-based approach to detecting network performance problems
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
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
A Set of Tools for Traffic Modeling, Analysis and Experimentation
TOOLS '00 Proceedings of the 11th International Conference on Computer Performance Evaluation: Modelling Techniques and Tools
How Does TCP Generate Pseudo-Self-Similarity?
MASCOTS '01 Proceedings of the Ninth International Symposium in Modeling, Analysis and Simulation of Computer and Telecommunication Systems
A user-friendly self-similarity analysis tool
ACM SIGCOMM Computer Communication Review
A pragmatic approach to dealing with high-variability in network measurements
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
More "normal" than normal: scaling distributions and complex systems
WSC '04 Proceedings of the 36th conference on Winter simulation
Wavelet analysis of long-range-dependent traffic
IEEE Transactions on Information Theory
A wavelet-based joint estimator of the parameters of long-range dependence
IEEE Transactions on Information Theory
A pragmatic approach to dealing with high-variability in network measurements
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
A decade of Internet research -- advances in models and practices
BT Technology Journal
An efficient technique to analyze the impact of bursty TCP traffic in wide-area networks
Performance Evaluation
Characterising a grid site's traffic
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Investigating self-similarity and heavy-tailed distributions on a large-scale experimental facility
IEEE/ACM Transactions on Networking (TON)
Investigating the distributional property of the session workload
Journal of Web Engineering
Semantic compression of TCP traces
NETWORKING'06 Proceedings of the 5th international IFIP-TC6 conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications Systems
A prediction method of network traffic using time series models
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
Review: A critical look at power law modelling of the Internet
Computer Communications
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We re-examine the same TCP trace that was used by Veres et al. [A. Veres, M. Boda, The chaotic nature of TCP congestion control, in: Proceedings of the IEEE INFOCOM, 2000] to claim that TCP creates self-similar traffic. A careful reassessment of their data analysis shows that this claim is not justified and suggests that the TCP trace in question is not consistent with (asymptotic second-order) self-similarity or long-range dependence (LRD). We illustrate the reasons that led to the claim in [A. Veres, M. Boda, The chaotic nature of TCP congestion control, in: Proceedings of the IEEE INFOCOM, 2000] and provide some practical guidelines for assessing a statistical characteristic of trace data such as LRD that is defined in strictly asymptotic terms. Our conclusion is in full agreement with the findings obtained from analyzing a much longer TCP trace (resulting from repeating the same simulation as in [A. Veres, M. Boda, The chaotic nature of TCP congestion control, in: Proceedings of the IEEE INFOCOM, 2000], but running it for a longer period) and with analytical results derived from a detailed Markovian model of TCP. These results show that the traffic generated by a long-lived TCP connection, while exhibiting pronounced correlations over a predictable finite range of time-scales, cannot be (asymptotically second-order) self-similar or exhibit LRD. Our work serves as a reminder of the importance of careful trace analysis and detailed examination (and cross-validation) of alternative explanations when establishing or characterizing the generality of any particular finding about Internet traffic.