Publication | Open Access
On the propagation of long-range dependence in the Internet
85
Citations
25
References
2000
Year
Congestion Control AlgorithmInternet Traffic AnalysisEngineeringTcp StreamNetwork AnalysisInternet ModelingNetwork PerformanceInformation PropagationSocial Network AnalysisNetwork FlowsComputer ScienceNetwork ScienceNetwork AlgorithmTcp Congestion ControlEdge ComputingNetwork Traffic ControlLong-range DependenceNetwork Traffic MeasurementCongestion Control
This paper analyzes how TCP congestion control can propagate self-similarity between distant areas of the Internet. This property of TCP is due to its congestion control algorithm, which adapts to self-similar fluctuations on several timescales. The mechanisms and limitations of this propagation are investigated, and it is demonstrated that if a TCP connection shares a bottleneck link with a self-similar background traffic flow, it propagates the correlation structure of the background traffic flow above a characteristic timescale. The cut-off timescale depends on the end-to-end path properties, e.g., round-trip time and average window size. It is also demonstrated that even short TCP connections can propagate long-range correlations effectively. Our analysis reveals that if congestion periods in a connection's hops are long-range dependent, then the end-user perceived end-to-end traffic is also long-range dependent and it is characterized by the largest Hurst exponent. Furthermore, it is shown that self-similarity of one TCP stream can be passed on to other TCP streams that it is multiplexed with. These mechanisms complement the widespread scaling phenomena reported in a number of recent papers. Our arguments are supported with a combination of analytic techniques, simulations and statistical analyses of real Internet traffic measurements.
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