Statistical analysis and simulation study of video teleconference traffic in ATM networks

Some of the source modeling and performance issues related to providing video teleconference services over asynchronous transfer mode (ATM) networks were studied. Under certain circumstances, traffic periodicity (due to the constant video frame rate) can cause different sources with identical statistical characteristics to experience cell-loss rates which can differ by several orders of magnitude. Some of this source-periodicity effect can be mitigated by appropriate buffer scheduling. For the video teleconference sequence analyzed (without scene changes or scene cuts and with moderate motion), the number of cells per frame is not normally distributed. Instead, it follows a gamma (or negative binomial) distribution. For traffic studies, an autoregressive model of order 2 and a two-state Markov chain model either underestimate or overestimate the occurrence of frames with a large number of cells, and these frames are a primary factor in determining cell-loss rates. The order-2 autoregressive model, however, fits the data well in a statistical sense. A multistate Markov chain model which can be derived from three traffic parameters (mean, correlation, and variance) is sufficiently accurate for use in traffic studies