Application of sampling methodologies to network traffic characterization
SIGCOMM '93 Conference proceedings on Communications architectures, protocols and applications
On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
Experimental queueing analysis with long-range dependent packet traffic
IEEE/ACM Transactions on Networking (TON)
Long-lasting transient conditions in simulations with heavy-tailed workloads
Proceedings of the 29th conference on Winter simulation
Self-similarity and heavy tails: structural modeling of network traffic
A practical guide to heavy tails
Deriving traffic demands for operational IP networks: methodology and experience
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
Trajectory sampling for direct traffic observation
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
Real-time estimation of the parameters of long-range dependence
IEEE/ACM Transactions on Networking (TON)
New directions in traffic measurement and accounting
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Charging from sampled network usage
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Adaptive random sampling for load change detection
SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Properties and prediction of flow statistics from sampled packet streams
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
Estimating flow distributions from sampled flow statistics
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Lévy flights and fractal modeling of internet traffic
IEEE/ACM Transactions on Networking (TON)
FGN based telecommunication traffic models
WSEAS Transactions on Computers
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Techniques for sampling Internet traffic are very important to understand the traffic characteristics of the Internet [A. Feldmann, A. Greenberg, C. Lund, N. Reingold, J. Rexford, F. True, Deriving traffic demands for operational ip networks: methodology and experience, in: Proc. ACM SIGCOMM'00, August 2000, pp. 257-270; N.G. Duffield, M. Grossglauser, Trajectory sampling for direct traffic observation, in: Proc. ACM SIGCOMM'00, August 2000, pp. 271-282]. In spite of all the research efforts on packet sampling, none has taken into account of self-similarity of Internet traffic in devising sampling strategies. In this paper, we perform an in-depth, analytical study of three sampling techniques for self-similar Internet traffic, namely static systematic sampling, stratified random sampling and simple random sampling. We show that while all three sampling techniques can accurately capture the Hurst parameter (second order statistics) of Internet traffic, they fail to capture the mean (first order statistics) faithfully. We also show that static systematic sampling renders the smallest variation of sampling results in different instances of sampling (i.e., it gives sampling results of high fidelity). Based on an important observation, we then devise a new variation of static systematic sampling, called biased systematic sampling (BSS), that gives much more accurate estimates of the mean, while keeping the sampling overhead low. Both the analysis on the three sampling techniques and the evaluation of BSS are performed on synthetic and real Internet traffic traces. Our performance study shows that BSS gives a performance improvement of 40% and 20% (in terms of efficiency) as compared to static systematic and simple random sampling.