№2, 2017


Ramiz H. Shikhaliyev

Traffic modeling allows evaluating the performance and capabilities of the network, as well as assessing the requirements presented to them. In the literature, various approaches were proposed for simulating the network traffic. However, there is no a single model that can simulate the traffic of all existing networks. Thus, the analysis of the characteristics of existing network traffic models, the selection of suitable models for certain network architectures, and the correct modeling of traffic is of great importance. This article analyzes some widely used models of network traffic (pp.88-93).

Keywords: network traffic models, Poisson model, Pareto model, Weibull model, Markov model, ON-OFF model, Markov modulated Poisson process, Autoregressive model.
  • Adas A. Traffic Models in Broadband Networks, IEEE Communications Magazine, 1997, 35, no.7, pp.82–89.
  • Becchi M. From Poisson Processes to Self-Similarity: a Survey of Network Traffic Models. Technical report, Citeseer, 2008.
  • Chandrasekaran B. Survey of Network Traffic Models. www.cs.wustl.edu/~jain/cse567-06/ ftp/ traffic_models3.pdf
  • Chen T.M. Network Traffic Modeling. http://pdfs.semanticscholar.org/5091/ e0fb30f8ff 50ec47 f43affc2bf08fac5dff0.pdf
  • Jain R., Routhier S. Packet Trains - Measurements and a New Model for Computer Network Traffic // IEEE JSAC, 1986, vol.4, no.6, pp.986–995.
  • Gusella R. A Measurement Study of Diskless Workstation Traffic on an Ethernet, IEEE Transactions on Communications, 1990, vol.38, no.9, pp.1557–1568.
  • Fowler H., Leland W. Local Area Network Traffic Characteristics, with Implications for Broadband Network Congestion Management, IEEE JSAC, 1991, vol.9, no.7, pp.1139–1149.
  • Danzig P., Jamin S., Ca´sceres R., Mitzel D., Estrin D. An Empirical Workload Model for Driving Wide-area TCP/IP Network Simulations, Internet-working: Research and Experience, 1992, vol.3, no.1, pp.1–26.
  • Leland W., Taqqu M., Willinger W., Wilson D. On the Self-Similar Nature of Ethernet Traffic (Extended Version), IEEE/ACM Transactions on Networking, 1994, 2, no.1, pp.1–15.
  • Willinger W., Paxson V., Taqqu M.S. Self-similarity and Heavy Tails: Structural Modeling of Network Traffic. In A Practical Guide to Heavy Tails: Statistical Techniques and Applications, Adler, R., Feldman, R., and Taqqu, M.S., editors, Birkhauser, 1998.
  • Paxson V., Floyd S. Wide-area Traffic: The Failure of Poisson Modeling, IEEE/ACM Transactions on Networking, 1995, pp.226–244.
  • Riedi R.H., Willinger W. Towards an improved understanding of network traffic dynamics. Self-similar Network Traffic and Performance Evaluation, Wiley, 2000, chapter 20, pp.507–530.
  • http://en.wikipedia.org/wiki/Pareto_distribution
  • http://en.wikipedia.org/wiki/Weibull_distribution
  • Yannaros N. Weibull renewal  processes //Annals of the Institute of Statistical Mathematics, 1994, vol.46, no.4, pp 641–648.
  • http://en.wikipedia.org/wiki/Heavy-tailed_distribution
  • Mohammed A.M., Agamy A.F. A Survey on the Common Network Traffic Sources Models // International Journal of Computer Networks, 2011, vol.3, no.2, pp.103–115.
  • Hlavacs H., Kotsis G., Steinkellner C. Traffic source modeling. Technical Report No. TR- Institute of Applied Computer Science and Information Systems University of Vienna, 1999.
  • Dainotti A., Pescapé A., Rossi P.S., Palmieri F., Ventre G. Internet traffic modeling by means of Hidden Markov Models, Computer Networks, 2008, vol.52, pp.2645–2662.
  • Willinger W., Leland W.E., Taqq M.S., Wilson D.V. On the self-similar nature of Ethernet traffic. ACM SIGCOMM, 1993.
  • Rolland C., Ridoux J., Baynat B. ON/OFF models to capture IP traffic structure, Student Workshop INFOCOM 2006.
  • Barford P., Crovella M. Generating Representative Web Workloads for Network and Server Performance Evaluation, In Proceedings of the 1998 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, 1998, pp.151–160.
  • Osaki S. Applied Stochastic System Modeling, Business & Economics, 2012, 269 p.
  • Li B., De Moor B. Information  measure  based stochastic  system identification  of ATM network  traffic, In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal1999, vol.5, pp.2683–2686.
  • Muscarielloa L., Mellia M., Meo M., Marsana M.A., Lo Cigno R. Markov models of internet traffic and a new hierarchical MMPP model // Computer Communications, 2005, 28, no.16, pp.1835–1851.
  • Scott S.L., Smyth P. The Markov Modulated Poisson Processand Markov Poisson Cascade with Applications to Web Traffic Modeling: www.datalab.uci.edu/papers/ScottSmythV7.pdf
  • Autoregressive Models. www2.stat.duke.edu/~km68/materials/214.8%20(ARp).pdf
  • Moving average models. www.otexts.org/fpp/8/4
  • Alonso A.M. Garc´ıa-Martos C. Time Series Analysis: Autoregressive, MA and ARMA processes. www.etsii.upm.es/ingor/estadistica/Carol/TSAtema4petten.pdf