We develop call admission policies for statistically multiplexing prerecorded sources over a bufferless transmission link. Our model is appropriate for video on demand, as well as other on-demand multimedia applications. In particular, we allow users to specify when the sources begin transmission; we also allow the user to invoke VCR actions such as pause and temporal jumps. We suppose that the quality of service (QoS) requirement allows for a small amount of packet loss. We develop a stochastic model which captures the random phases of the sources. We then apply large deviation theory to our model to develop global admission rules. The accuracy of the large deviation approximation is verified with simulation experiments employing importance sampling techniques. We also propose a refined admission rule which combines the global test and a myopic test. Numerical results are presented for the Star Wars trace; we find that the statistical multiplexing gain is potentially high and often insensitive to the QoS parameter. Finally, we develop efficient schemes for the real-time implementation of our global test. In particular, we demonstrate that the Taylor series expansion of the logarithmic moment generating function of the frame size distribution allows for fast and accurate admission decisions.
- Call admission
- Packetized video
- Prerecorded sources
- Video on demand
ASJC Scopus subject areas
- Computer Networks and Communications
- Electrical and Electronic Engineering