By Topic

Modeling video traffic using M/G/∞ input processes: a compromise between Markovian and LRD models

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Krunz, M.M. ; Dept. of Electr. & Comput. Eng., Arizona Univ., Tucson, AZ, USA ; Makowski, A.M.

Statistical evidence suggests that the autocorrelation function p(k) (k=0,1,...) of a compressed-video sequence is better captured by p(k)=e-β√k than by p(k)=k=e-βlogk (long-range dependence) or p(k)=e-βk (Markovian). A video model with such a correlation structure is introduced based on the so-called M/G/∞ input processes. In essence, the M/G/∞ process is a stationary version of the busy-server process of a discrete-time M/G/∞ queue. By varying G, many forms of time dependence can be displayed, which makes the class of M/G/∞ input models a good candidate for modeling many types of correlated traffic in computer networks. For video traffic, we derive the appropriate G that gives the desired correlation function p(k)=e-β√k. Though not Markovian, this model is shown to exhibit short-range dependence. Poisson variates of the M/G/∞ model are appropriately transformed to capture the marginal distribution of a video sequence. Using the performance of a real video stream as a reference, we study via simulations the queueing performance under three video models: our M/G/∞ model, the fractional ARIMA model (which exhibits LRD), and the DAR(1) model (which exhibits a Markovian structure). Our results indicate that only the M/G/∞ model is capable of consistently providing acceptable predictions of the actual queueing performance. Furthermore, only O(n) computations are required to generate an M/G/∞ trace of length n, compared to O(n2) for an F-ARIMA trace

Published in:

Selected Areas in Communications, IEEE Journal on  (Volume:16 ,  Issue: 5 )