The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Effect of the Variable Packet Size on LRD Characteristic of the MMPP Traffic Model

  • 이강원 (서울산업대학교 산업정보시스템공학과) ;
  • 권병천 (대한항공 정보시스템실)
  • Published : 2008.01.31
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Abstract

The effect of the variable packet size on the LRD characteristic of the MMPP traffic model is investigated. When we generate packet traffic for the performance evaluation of IP packet network, MMPP model can be used to generate packet interarrival time. And a random length of packet size from a certain distribution can be assigned to each packet. However, there is a possibility that the variable packet size might change the LRD characteristic of the original MMPP model. In this study, we investigate this possibility. For this purpose the 'refined traffic' is defined, where packet arrival time is generated according to the MMPP model and a random packet length from a specific distribution is assigned to each generated packet. Hurst parameter of the refined traffic is estimated and compared with the original Hurst parameter, which is the input parameter of the MMPP model. We also investigate the effect of the packet size distribution on the queueing performance of the MMPP traffic model and the relationship between the Hurst parameter and queueing performance.

Keywords

References

  1. IEEE 802.16 Broadband Wireless Access System, IEEE 802.16.3c-01/30r1, March 2001
  2. A. Erramilli, O. Narayan, W. Willinger, "Experimental queueing analysis with long-range dependent packet traffic", Bellcore
  3. K. Park, G. Kim, M. Crovella, "On the effect of traffic self-similarity on network performance", SPIE, 1997
  4. M. Crovella, A. Bestavros, "Explaining world wide web traffic self-similarity", Boston University, October 1995
  5. A. Anderson, B. Nielsen, "A Markovian approach for modeling packet traffic with long-range dependence", IEEE JSAC, vol.16, no.5, pp.719-732, June 1998
  6. T. Yoshihara, S. Kasahara, Y. Takahasi, "Practical time-scale fitting of self-similar traffic with Markov-modulated Poisson process", Telecommunication Systems, vol.17, no.1-2, pp.185-211, 2001 https://doi.org/10.1023/A:1016616406118
  7. P. Salvador, A. Pacheco, R. Vaiadas, "Multiscale fitting procedure using Markov modulated Poisson process", Telecommunication Systems, vol.23, no.1-2, pp.123-148, June 2003 https://doi.org/10.1023/A:1023672904130
  8. W. Leland, M. Taqqu, W. Willinger, D. Wilson, "On the self-similar nature of Ethernet traffic (extended version)", IEEE/ACM Transaction on Networking, vol.2, no.1, pp.1-15, Feb 1994 https://doi.org/10.1109/90.282603
  9. V.Paxon, S.Floyd, "Wide-area traffic: the failure of Poisson modeling", IEEE/ACM Transactions on networking, vol.3, no.3, pp.226-244, 1995 https://doi.org/10.1109/90.392383
  10. W. Willinger, M.S. Taqqu, R. Sherman, D.V. Wilson, "Self-similarity through high variability: statistical analysis of ethernet LAN traffic at the source level", IEEE/ACM Transaction on Networking, vol.5, no.1, pp.79-86, 1997
  11. I. Norros, "On the use of fractional Brownian motion in the theory of connectionless networks", IEEE JSAC, vol. 13, pp.953-962, 1995
  12. S. Ma, C. Ji, "Modeling heterogeneous network traffic in wavelet domain", IEEE/ACM Transaction on Networking, vol.9, no.5, pp.634-649, 2001 https://doi.org/10.1109/90.958331
  13. R.J. Mondragon, J.M. Pitts, D.K. Arrowsmith, "Chaotic intermittency-sawtooth map model of aggregated self-similar traffic stream", Electronic Letters, vol.36, no.2, pp.184-186, 2000 https://doi.org/10.1049/el:20000184
  14. M. Krunz, A. Makowski, "A source model for VBR video traffic based on M/G/infinity input processes", IEEE Infocom '98, SF, CA, USA, pp.1441-1448, April 1998
  15. M. Grossglauser, J.C. Bolot, "On the relevance of long-range dependence in network traffic", IEEE/ACM Transactions on Networking, vol.7, no.5, pp.629-640, Oct 1999 https://doi.org/10.1109/90.803379
  16. A. Nogueria, R. Valadas, "Analyzing the relevance time scale in a network of queues", SPIE, August 2001
  17. H. Riedi, D.V. Vehel, "A multifractal wavelet model with application to data traffic," IEEE Transaction on Info. Theory, vol.45, no.4, pp.992-1018, 1999 https://doi.org/10.1109/18.761337
  18. R. Ritke, X. Hong, M. Gerla, "Contradictory relationship between Hurst atameter and queueing performance', Computer Science Department, UCLA, 2004
  19. M. Trovero, "Long-range dependence: a light tale for practitioner", Oct 2003
  20. A. Nogueira, P. Salvador, R. Valadas, "Fitting self-similar traffic by a superposition of MMPPs modeling the distribution at multiple time scales", IEICE Trans. on Communications, vol.E27-B, no.3, pp.678-688, March 2004
  21. L. Muscariello, M. Mellia, M. Meo , A. M. Marsan, R.M. Cigno, "Markov models of internet traffic and a new hierarchical MMPP model", Computer Communication, vol.28, pp.1835-1851, 2005 https://doi.org/10.1016/j.comcom.2005.02.012
  22. G. Dan, V. Fodor, G. Karlsson, "Packet size distribution: an aside", QoS-IP, pp.75-87, 2005
  23. P. Salvador, A. Pacheco, R. Vaiadas, "Modeling IP traffic: joint characterization of packet arrivals and packet sizes using BMAPs", Computer Networks, vol.44, pp.335-352, 2004 https://doi.org/10.1016/j.comnet.2003.10.004