Jitter-based delay-boundary prediction of wide-area networks

The delay-boundary prediction algorithms currently Implemented by transport protocols are lowpass filters based on autoregressive and moving average (ARMA) models. However, recent studies have revealed a fractal-like structure of delay sequences, which may not be well suited to ARMA models. In this paper, we propose a novel delay-boundary prediction algorithm based on a deviation-lag function (DLF) to characterize end-to-end delay variations. Compared to conventional algorithms derived from ARMA models, the new algorithm can adapt to delay variations more rapidly and share delay's robust high-order statistical information (jitter deviation) among competing connections along a common network path. Preliminary experiments show that it outperforms Jacobson's algorithm, which is based on an ARMA model, by significantly reducing the prediction error rate. To show the practical feasibility of the DLF algorithm, we also propose a skeleton implementation model.