A Bayesian framework-based end-to-end packet loss prediction in IP networks
Channel modelling in a network path is of major importance in designing delay sensitive applications. It is often not possible for these applications to retransmit packets due to delay constraints and they must therefore be resilient to packet losses. In this paper, we first establish an association between traffic delays and the queue size at a network gateway. A novel method for predicting packet losses is then proposed that is based on the correlation between the packet losses and the variations in the end-to-end time delay observed during transmission. We show that this makes it possible to predict packet losses before they occur. The transmission of multimedia streams can then be dynamically adjusted to account for the predicted losses. As a result, better error-resilience can be provided for multimedia streams transmitting through a dynamic network channel. This means that they can provide an improved quality of transmission under the same network budget constraint. Experiments have been performed and preliminary results have shown that the method can provide a much smoother and more reliable transmission of data.