Novel approaches for online playout delay prediction in VoIP applications using time series models

Voice over IP (VoIP) applications requires a buffer at the receiver to minimize the packet loss due to late arrival. Several algorithms are available in the literature to estimate the playout buffer delay. Classic estimation algorithms are non-adaptive, i.e. they differ from more recent approaches basically due to the absence of learning mechanisms. This paper introduces two new formulations of adaptive algorithms for online learning and prediction of the playout buffer delay, the first one being based on the standard Box-Jenkins autoregressive model, while the second one being based on the feedforward and recurrent neural networks. The obtained results indicate that the proposed algorithms present better overall performance than the classic ones.