Proof of a fundamental result in self-similar traffic modeling
ACM SIGCOMM Computer Communication Review
Estimating the heavy tail index from scaling properties
Methodology and Computing in Applied Probability
Estimating flow distributions from sampled flow statistics
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Deterministic versus probabilistic packet sampling in the internet
ITC20'07 Proceedings of the 20th international teletraffic conference on Managing traffic performance in converged networks
Cluster processes: a natural language for network traffic
IEEE Transactions on Signal Processing
Wavelet analysis of long-range-dependent traffic
IEEE Transactions on Information Theory
Maximum likelihood estimation of the flow size distribution tail index from sampled packet data
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
On the statistical characterization of flows in Internet traffic with application to sampling
Computer Communications
Internet access traffic measurement and analysis
TMA'12 Proceedings of the 4th international conference on Traffic Monitoring and Analysis
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In this article, we address the problem of estimating the tail parameter of a flow size distribution from sampled packet traffic. Based on synthetic data, we perform a systematic comparison of several estimators proposed in the literature. In the course, we propose a variant to an existing method which takes into account some statistical a priori on the expected distribution. This adapted estimator shows a significantly improved performance, as compared to the others.