Burstiness Reduction of a Doubly Stochastic AR-Modeled Uniform Activity VBR Video
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32771
Burstiness Reduction of a Doubly Stochastic AR-Modeled Uniform Activity VBR Video

Authors: J. P. Dubois

Abstract:

Stochastic modeling of network traffic is an area of significant research activity for current and future broadband communication networks. Multimedia traffic is statistically characterized by a bursty variable bit rate (VBR) profile. In this paper, we develop an improved model for uniform activity level video sources in ATM using a doubly stochastic autoregressive model driven by an underlying spatial point process. We then examine a number of burstiness metrics such as the peak-to-average ratio (PAR), the temporal autocovariance function (ACF) and the traffic measurements histogram. We found that the former measure is most suitable for capturing the burstiness of single scene video traffic. In the last phase of this work, we analyse statistical multiplexing of several constant scene video sources. This proved, expectedly, to be advantageous with respect to reducing the burstiness of the traffic, as long as the sources are statistically independent. We observed that the burstiness was rapidly diminishing, with the largest gain occuring when only around 5 sources are multiplexed. The novel model used in this paper for characterizing uniform activity video was thus found to be an accurate model.

Keywords: AR, ATM, burstiness, doubly stochastic, statisticalmultiplexing.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1070779

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1350

References:


[1] D. Anick, D. Mitra, and M. Sondhi, "Stochastic Theory of Data- Handling System with Multiple Sources," Bell System Technical Journal, Vol. 61, No. 6, pp. 1871-1894, 1982.
[2] B. Maglaris, D. Anastassiou, P. Sen, G. Karlsson, and J. Robbins, "Performance Models of Statistical Multiplexing in Packet Video Communications," IEEE Trans. on Comm., Vol. 7, pp. 834-844, 1988.
[3] H. Saito, M. Kawarasaki, and H. Yamada, "An Analysis of Statistical Multiplexing in an ATM Transport Network," IEEE Journal on Selected Areas in Communication, Vol. 9, No. 3, pp. 359-367, 1991.
[4] H. Heffes and D. Lucantoni, "A Markov Modulated Characterisation of Packetized Voice and Data Traffic and Related Statistical Multiplexer Performance," IEEE J. on Sel. Areas in Comm, Vol. 4, pp. 856-867, 1986.
[5] N. Ohta, Packet Video: Modeling and Signal Processing, Artech House, London, 1994.
[6] T. Hou and A. Wong, "Queueing Analysis for ATM Switching of Mixed Continuous-Bit-Rate and Bursty Traffic," Proc. IEEE, pp. 660-667, 1990.
[7] C. Rosenberg, F. Guillemin, and R. Maxumdar, "New Approach for Traffic Characterisation in ATM Networks", IEEE Proceedings Communications, Vol. 142, No. 2, pp. 87-90, 1995.
[8] I. Habib and T. Saadwi, "Multimedia Traffic Characteristics in Broadband Networks," IEEE Comm. Magazine, pp. 48-54, 1992.
[9] L. Cuthbert and J. Sapanel, ATM: The Broadband Telecommunications Solution, IEE, London, 1993.
[10] R. Cramblitt and K. Parker, "Generation of Non-Rayleigh Speckle Distributions Using Marked Regularity Models," IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 46, No. 4, pp. 867 - 874, 1999.
[11] D. Snyder and M. Miller, "Random Point Processes in Time and Space," Springer-Verlag, NY, 1991.