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Approximated self-similar process for generation of ICT traffic

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Konferencja
Computer Applications in Electrical Engineering 2012 (23-24.04.2012; Poznań, Polska)
Języki publikacji
EN
Abstrakty
EN
Self-similar nature of ICT traffic causes big impact on queuing performance needed in providing a certain level of Quality of Service. Therefore, synthesis of fractal process for simulation and analysis purposes should be fast and accurate. In this article it is proposed how to simplify distribution of interarrivals in the renewal process in order to implement the inverse distribution technique to generate random variables. Proposed method improves simulation performance by reducing computational complexity leaving the accuracy almost unchanged.
Rocznik
Tom
Strony
233--239
Opis fizyczny
Bibliogr. 16 poz., rys.
Twórcy
  • West Pomeranian University of Technology
Bibliografia
  • [1] Elbiaze H., et al., ”A new structure-preserving method of sampling for predicting self-similar traffic”. Telecommunication Systems, 43, 265-277, 2010.
  • [2] Field A.J., Harder U., Harrison P.G., Measurement and Modelling of Self-similar Traffic in Computer Networks. IEE Proc-Commun., 151, 4 (Aug 2004), 355-386.
  • [3] He G., Gao Y., Hou J., Park K., A case for exploiting self-similarity of network traffic in TCP congestion control, Computer Networks, 45, 6 (Aug 2004), 743-766.
  • [4] Jelenkovic P.R., Lazar A.A., Semret M., Multiple time scales and subexponentiality in MPEG video streams. Proc. of IFIP-IEEE, Conference on Broadband Communications, 1996, 64-75.
  • [5] Leland W., Taqqu M., Willinger W., Wilson D., On the self-similar nature of Ethernet traffic (extended version). IEEE/ACM Transactions on Networking, 2, 1 (Feb 1994), 1-15.
  • [6] Lelarge M., Liu Z., Xia C.H., Asymptotic Tail Distribution of End-to-End Delay in Networks of Queues with Self-Similar Cross Traffic. IEEE INFOCOM 2004.
  • [7] Lin G.C., Suda T., On the impact of long-range dependent traffic in dimensioning ATM network buffer. Proc. Of IEEE INFOCOM, 1998.
  • [8] Medhi J., Stochastic models in queueing theory. Academic Press, 2003.
  • [9] Norros I., A storage model with self-similar input. Queueing Systems, 16, 1994, 387-396.
  • [10] Norros I., On the use of fractional Brownian motion in the theory of connectionless networks. IEEE Journal on Selected Areas in Communications, 13 (6), 1995.
  • [11] Parulekar M., Makowski A.M., Tail probabilities for a multiplexer with selfsimilar traffic. Proc. IEEE INFOCOM, 1996.
  • [12] Park K., Kim G.T., Crovella M.E., On the relationship between file sizes, transport protocols and self-similar network traffic. Technical report, Boston University, Computer Science Department, 1996.
  • [13] Paxson V., Fast, Approximate synthesis offractional Gaussian noise for generating self-similar network traffic. ACM SIGCOMM Computer Communication Review 27, 5 (Oct 1997), 5-18.
  • [14] Taralp T., Devetsikiotis M., Lambadaris I., Efficient fractional Gaussian noise generation using the spatial renewal process. Proceedings of the IEEE International Conference on Communications, Atlanta, GA, vol. 3 (Jun 1998), 1456-1460.
  • [15] Taqqu M., Willinger W., Scherman R., Proof of a Fundamental Result in Self-Similar Traffic Modeling. ACM SIGCOMM Computer Communication Review, 27, 2 (Apr 1997), 5-23.
  • [16] Yunhua R., Evaluation and estimation of second-order self-similar network traffic. Computer Communications 27 (2004), 898-904.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6e7ab39c-1cab-4b2d-a160-46c27da927b3
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