What are the implications of long-range dependence for VBR-video traffic engineering?

The authors explore the influence of long-range dependence in broadband traffic engineering. The classification of stochastic processes {X_t} into those with short or long-range dependence is based on the asymptotic properties of the variance of the sum S_m =X₁+X₂+···+X_m . Suppose this process describes the number of packets (or ATM cells) that arrive at a buffer; X_t is the number that arrive in the tth time slice (e.g., 10 ms). We use a generic buffer model to show how the distribution of S_m (for all values of m) determines the buffer occupancy. From this model we show that long-range dependence does not affect the buffer occupancy when the busy periods are not large. Numerical experiments show this property is present when data from four video conferences and two entertainment video sequences (which have long-range dependence) are used as the arrival process, even when the transmitting times are long enough to make the probability of buffer overflow 0.07. We generated sample paths from Markov chain models of the video traffic (these have short-range dependence). Various operating characteristics, computed over a wide range of loadings, closely agree when the data trace and the Markov chain paths are used to drive the model. From this, we conclude that long-range dependence is not a crucial property in determining the buffer behavior of variable bit rate (VBR)-video sources