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Detection and quantification of self- similarity in data traffic for prediction of performance of marine data file transfer

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Języki publikacji
EN
Abstrakty
EN
The time-sensitivity of large marine data files over a communication network necessitates accurate simulative prediction of the file transfer performance. Careful data traffic modelling is required to fit the actual traffic characteristics for subsequent generation of synthetic traffic traces and feeding them into a simulation model. Classical models have recently proved inadequate due to the discovery of self-similarity (fractal behaviour) in data traffic. This paper attempts to systematise the mathematical background of self-similarity and the ways it manifests itself in stochastic processes modelling data traffic. Relevance of self-similarity to traffic description and measurements is discussed. Results of a research effort at the Department of Marine Electronics of the Maritime Institute in Gdansk are described, which focus on the development of a software tool for detection and quantification of self- similarity in observed or synthetically generated data traffic.
Słowa kluczowe
Rocznik
Strony
29--48
Opis fizyczny
Bibliogr. 21 poz., rys., tab.
Twórcy
autor
  • Department of Marine Electronics Maritime Institute, Gdańsk, Poland
Bibliografia
  • [1] Addie, R.G. and Zuckerman, M., 1998, Broadband Traffic Modelling: Simple Solutions to Hard Problems, IEEE Comm. Mag. 8.
  • [2] Crovella, M.E. and Bestavros, A., 1997, Self-similarity in World Wide Web Traffic: Evidence and Possible Causes, IEEFJACM Trans. on Networking 5(6).
  • [3] Erramilli, A., Pruthi, P. and Willinger, W., 1994, Application of Fractals in Engineering for Realistic Traffic Processes, Proc. 14'h Int. Teletraffic Congress, Sophia-Antipolis, France.
  • [4] Fiorini, P.M., Crovella, M. and Lipsky, L., 1998, On the Connection between Power-Tail Distributions and Long-Range Dependencies, available from crovella@cs.bu.edu
  • [5] Gajewski, J., and Staśkiewicz, A., 1998, Validation of Hydrodynamic Models of the Baltic Sea in Polish Waters- HIROMB as an Example , Bull. Mar. lnst., XXV, (2).
  • [6] Jędruś S. 1999, Modelling of packet traffic intensity in computer networks using multi-fractal measures, Ph.D. dissertation, Inst. of Theoretical and Applied Informatics, Gliwice. [ln. Polish].
  • [7] Karlsson, P. and Arvidsson, A., 1999, Traffic Modelling of TCP/IP over ATM, draft for 16th Int. Teletraffic Congress, Edinburgh, UK. ·
  • [8] Leland, W.E., Taqqu, M.S., Willinger, W. and Wilson D.V., 1993, On the Self Similar Nature on Ethernet Traffic (Extended Version), draft, ftp://ftp.bellcore.com/pub/world/weltome.ps.Z.
  • [9] Leland, W.E., Taqqu, M.S., Willinger, W. and Wilson D.V., 1994, On the Self Similar Nature on Ethernet Traffic (Extended Version), IEEE/ACM Trans. on Networking 2(1).
  • [10] Mandelbrot, B., 1983, The Fractal Geometry of Nature, Freeman, New York.
  • [11] Molnar, S. and Vidacs, A., 1997, On Modelling and Shaping Self-similar ATM Traffic, Proc. 15'h Int. Teletraffic Congress, Washington D.C.
  • [12] Norros, I., 1995, On the Use of Fractional Brownian Motion in the Theory of Connectionless Networks, IEEE J. Selected Areas In Comm., 13 (6).
  • [13] Park, K., Kim, G. and Crovella, M., 1997, On the Effect of Traffic Self-similarity on Network Performance, Proc. SPIE Int. Con f. on Performance and Control of Network Systems.
  • [14] Paxson, V. and Floyd, S., 1995, Wide Area Traffic: The Failure of Poisson Modelling, IEEE/ACM Trans. on Networking 3(3).
  • [15] Roberts, J., Mocci, U. and Virtamo, J. (eds.), 1996, Broadband Network Teletraffic, SpringerVerlag, Berlin Heidelberg.
  • [16] Ryu, B., 1997, Fractal Network Traffic Modelling: Past, Present and Future, Proc. 35 Allerton Conf. on Comrn., Control and Computing, http://www.wins.hrl.com/peoplelryu/fsndpMS95.ps.gz
  • [17] Ryu, B. and Lowen, S.B ., 1998, Point Process Models for Self-Similar Network Traffic with Applications, [in] Neuts, M. (ed.), Stochastic Models 14 (3), http://www.wins.hrl.com/peoplelryu/srn98. ps.gz
  • [18] Taqqu, M.S., Teverowsky, V. and Willinger, W., 1995: Estimators for Long-Range Dependence: an Empirical Study, Fractals 3(4), http://math.bu.edu/people/murad/pub/estimators-posted.ps
  • [19] Taqqu, M.S., Willinger, W. and Sherman, R., 1997, Proof of a Fundamental Result in SelfSimilar Traffic Modelling, Computer Comm. Review, 27, http://math.bu.edu/people/murad/ pub/ccr97 -onoff-posted.ps
  • [20] Taralp, T., Devetsikiotis, M. and Lambadaris, 1., 1998, Traffic Characterisation for QoS Provisioning in High-Speed Networks, Proc. Hawai'i Int. Conf. On System Sciences, ftp://www.sce.carleton.ca/pub/bbnlab/doc026.pdf
  • [21] Willinger, W., Taqqu, M.S ., Sherman, R. and Wilson, D.V., 1997, Self-similarity Through High Variability: Statistical Analysis of Ethernet LAN Traffic at the Source Level, IEEEIACM Trans. on Networking 5(1).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0480cbc9-c8c3-4060-b683-fd75548e1723
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