Abstract
The scaling behavior has been discovered in the past decade, which has provided hope that mathematical models can be found to describe the nature of the traffic. Similarly to long-range dependence (LRD), nonstationarity is also one of vital characteristics of network traffic. In this paper, a novel traffic model is proposed based on that the traffic aggregation behavior is abstracted in hierarchical way. The traffic model is focused on the burst traffic rate. Firstly, the burst size of output aggregated flow by edge device of a network domain is derived by pseudo queue system methods. And, the nonstationarity of input traffic is developed by a generalized fractal Gaussian noise process, which is constructed by a large number of train traffic series. They are Poisson arrival and their lifetime is exponential distribution. The model has a good performance of fitting to real traffic data within multi-scale for long time, which is illuminated by simulated results.
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References
Abry, P., Baraniuk, R., Flandrin, P., Riedi, R., Veitch, D.: The Multisclae Nature of Network Traffic: Discovery, Analysis, and Modelling. IEEE Signal Processing Magzine 19(3), 28–46 (2002)
Hellerstein, J.L., Zhang, F., Shababuddin, P.: An Approach to Predictive Detection for Service Management. In: Proc. of the Intel. Conf. on Systems and Network Management (1999)
Cao, J., Cleceland, W.S., Lin, G., Sun, D.X.: On the Nonstationarity of Internet Traffic. In: Proc. SIGMETRICS/Performance 2001, Joint International Conference on Measurements and Modeling of Computer Systems, pp. 102–112. ACM, Cambridge (2001)
Cruz, R.L.: A Calculus for Network Delay, Part I: Network Elements in Isolation. IEEE Trans. on Information Theory 37(1), 114–131 (1991)
Cruz, R.L.: A Calculus for Network Delay, Part II: Network Analysis. IEEE Trans. on Information Theory 37(1), 132–141 (1991)
Eckberg, A.E.: Approximations for Burst (and Smoothed) Arrival Queuing Delay Based on Generalized Peakedness. In: Proc. 11th International Teletraffic Congress, Kyoto (1985)
Eick, S.G., Massey, W.A., Whitt, W.: The Physical of the Queue. Operations Research. Journal of the Operations Research Society, 731–741 (1993)
NLANR network traffic packet header traces, http://pma.nlanr.net/Traces/
Liu, C., Wiel, S.V., Yang, J.: A Nonstationary Traffic Train Model for Fine Scale Inference From Coarse Scale Counts. IEEE Journal on Selected Areas in Communications: Internet and WWW Measurement, Mapping, and Modeling 21(6), 895–907 (2003)
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Wei, J., Wu, J. (2005). Nonstationarity of Network Traffic Within Multi-scale Burstiness Constraint. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3802. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596981_144
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DOI: https://doi.org/10.1007/11596981_144
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30819-5
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