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The Self-Similarity Measurement for Internet Traffic based on Wavelet-analysis in G/G/1 Queueing System
|關鍵字:||Self-similar;自相似性;Wavelet-based analysis;G/G/1;Superimposition;Inter-arrival time;Packet size;小波分析;G/G/1;重疊;封包間隔時間;封包大小||出版社:||通訊工程研究所||引用:|| P. Abry, P. Gon¸calv`es, and P. Flandrin, “Wavelet-based spectral analysis of 1=f processes,” in Proc. IEEE-ICASSP'93, 1993, pp. III.237-III.240.  P. Abry an D. Veitch, “Wavelet Analysis of Long-Range-Dependent Traffic,” IEEE Trans. Inform. Theory, vol. 44, pp. 2-15, Jan. 1998.  J. Cao, W. S. Cleveland, D. Lin, and D. X. Sun, “On the Nonstationarity of Internet Traffic,” ACM SIGMETRICS, pp. 102-112, 2001.  J. Cao, W. S. Cleveland, D. Lin, and D. X. Sun, “The Effect of Statistical Multiplexing on the Long-Range Dependence of Internet Packet Traffic,” Tech. Rep., Bell Labs, Murray Hill, NJ, 2002  J. Cao, W. S. Cleveland, D. Lin and D. X. Sun, “Internet Traffic Tends Toward Poisson and Independence as the Load Increase,” Technical report, Bell Labs, 2001.  M. Crovella and A. Bestavros, “Self-similar in World-Wide Web Traffic: Evidence and Possible Causes,” in Proc. of ACM Sigcomm'96, May.1996.  L. J. de la Cruz, E. Pallares, and J. J. Alins y Jorge Mata, “Self-similar traffic generation using a fractional ARIMA model. Application to the VBR MPEG video traffic,” in Telecommunications Symposium, 1998.  A. Erramilli, O. Narayan, and W. Willinger, “Experimental Queueing Analysis with Long-Range Dependent Packet Traffic,” IEEE/ACM Trans. Networking, vol. 4, no. 2, pp. 209-223, Apr. 1996.  Y. Fan and N. D. Georganas ,”On Merging and Splitting of Self-similar Traffic in High Speed Networks,” in Proc. of ICCC'95, Seoul, Korea, Aug. 1995.  P. Flandrin, “Wavelet analysis and synthesize of fractional Brownian motion,” IEEE Trans. Inform. Theory, vol. 38, pp. 910-916, Mar. 1992.  Available FTP: tracer.csl.sony.co.jp Directory: pub/mawi/samplepoint-B/  Available FTP: ita.ee.lbl.gov Directory: traces/  J. R. M Hosking, “Fractional difference,” Biometrika, pp165-176, 1981.  B. Tsybakov, and N. D. Georganas, “On Self-Similar Traffic in ATM Queue: Definition, Overflow Probability Bound, and Cell Delay Distribution, ” IEEE Trans. On Networking, Vol.5, No. 3, June 1997.  L. Kleinrock, Queueing Systems, vol. 1. New York: Wiley, 1975.  W. Leland, M. Taqqu, W. Willinger, and D. Wilson, “On the Self-Similar Nature of Ethernet Traffic (Extended Version),” IEEE/ACM Transactions on Networking, 2(1), pp. 1-15, February 1994.  S. Mallat, “A theory for multiresolution signal decomposition: The wavelet representation,” IEEE Trans. Pattern Anal. Machine Intell, vol. 11, pp. 674-693, July 1989.  Y. C. Ouyang, L. B. Yeh, “Predictive bandwidth control for MPEG video: a wavelet approach for self-similar parameters estimation”, Proceedings of ICC 2001, pp 1551-1555, June 2001.  V. Paxson and S. Floyd, “Wide-Area Traffic: The Failure of Poisson Modeling,” IEEE/ACM Transaction on Networking, 3:226-244, 1995  K. Sayood, Introduction to Data Compression. San Mateo, CA: Morgan Kaufmann, 2000.  T. Karagiannis, M. Molle, M. Faloutsos and A. Broido, “A Nonstationary Poisson View of Internet Traffic,” IEEE Conference of the IEEE Computer and Communications Societies, 2004  W. Stallings, High-speed Networks and Internets, Prentice-Hall, New Jersey, 2002.||摘要:||
Network devices put packets on an internet link, and multiplex, or superimpose the packet form different active connections. Network arrivals are often modeled as Poisson processes for analytic simplicity, even thought a number of traffic studies have shown that packet inter-arrivals are not exponentially distribution. The notion of self-similarity has been shown to apply to wide-area and local-area network traffic. In recent years, many researchers reexamine the Poisson distribution model for traffic assumption and they point out that once the connection load is sufficiently large, the network begins pushing back on the attraction to Poisson and independence by causing queueing on the link-input router. Therefore, performance analysis of queueing system in long-range dependence traffic is needed to design a reliable network under the tremendous growth of internet traffic. In this thesis, we use a synthesize inter-arrival time distribution form ARIMA model and measure the sensitivity of output performance under various degrees of long-range dependent packet arrival. Experimental results show that packet arrival processes appear better modeled as self-similar processes.
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