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

Source modeling and performance issues are studied using a long (30 min) sequence of real video teleconference data. It is found that traffic periodicity can cause different sources with identical statistical characteristics to experience differing cell-loss rates. For a single-stage multiplexer model, some of this source-periodicity effect can be mitigated by appropriate buffer scheduling and one effective scheduling policy is presented. For the sequence analyzed, the number of cells per frame follows a gamma (or negative binomial) distribution. The number of cells per frame is a stationary stochastic process. For traffic studies, neither an autoregressive model of order two nor a two-state Markov chain model is good because they do not model correctly the occurrence of frames with a large number of cells, which are a primary factor in determining cell-loss rates. The order two autoregressive model, however, fits the data well in a statistical sense. A multistate Markov chain model that can be derived from three traffic parameters is sufficiently accurate for use in traffic studies