Modeling and queueing analysis of variable-bit-rate coded video sources in ATM networks

Traffic models and queueing performance of variable-bit-rate (VBR) video sources in an asynchronous transfer mode (ATM) network are studied. A discrete-time discrete-state Markov chain is used to model the aggregate video traffic with each VBR-coded source being modeled by a renewal process, which has been successfully applied in the analysis of packet voice traffic. Three different methods including the stationary-interval (SI) method, the asymptotic method (ASM), and the hybrid method for queueing network analyzer (QNA) are used to approximate the average queue size. Results for different traffic conditions and different number of VBR sources are compared with the simulation results. It can be observed that as the number of sources increases the aggregate traffic becomes more predictable and the congestion at the common queue becomes smaller. This result verifies the fact that multiplexing a large number of identical video sources on a single high speed link statistically yields significant bandwidth saving. It is also interesting to note that the SI method provides an upper bound and the ASM method yields a lower bound for the average queue size for the type of traffic used in the study. When the number of VBR sources increases, the result deviates from the SI method and approaches the ASM method. In general, the QNA method provides a close match to the simulation result