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Proceedings Paper

Estimating degree of mixing in statistically multiplexed data
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Paper Abstract

This paper examines the problem of determining the degree of mixing of two independent and different types of traffic streams from observations of their statistically multiplexed stream. A common example of a pair of such different stream types in networks would be one conforming to the conventional Poisson model and the other obeying long-range dependence characterized by a heavy-tailed distribution. We provide an expression for the probability density function of the inter-arrival time of the mixed stream in terms of those of the input streams for the general case. An approach is provided to estimate input parameters from the first and second order statistics of the output traffic for the specific case of multiplexing Poisson and heavy-tailed processes.

Paper Details

Date Published: 12 May 2006
PDF: 8 pages
Proc. SPIE 6248, Wireless Sensing and Processing, 62480V (12 May 2006); doi: 10.1117/12.672075
Show Author Affiliations
Rajesh Narasimha, Georgia Institute of Technology (United States)
Raghuveer M. Rao, Rochester Institute of Technology (United States)
Sohail Dianat, Rochester Institute of Technology (United States)


Published in SPIE Proceedings Vol. 6248:
Wireless Sensing and Processing
Raghuveer M. Rao; Sohail A. Dianat; Michael D. Zoltowski, Editor(s)

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