Title :
Jitter-based delay-boundary prediction of wide-area networks
Author :
Li, Qiong ; Mills, David L.
Author_Institution :
Dept. of Wireless Commun. & Networking, Philips Res., Briarcliff Manor, NY, USA
fDate :
10/1/2001 12:00:00 AM
Abstract :
The delay-boundary prediction algorithms currently implemented by transport protocols are lowpass filters based on autoregressive and moving average (ARMA) models. However, previous studies have revealed a fractal-like structure of delay sequences, which may not be well suited to ARMA models. We propose a novel delay-boundary prediction algorithm based on a deviation-lag function (DLF) to characterize the 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 the 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 (1988) 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
Keywords :
Poisson distribution; autoregressive moving average processes; delays; fractals; higher order statistics; jitter; prediction theory; transport protocols; wide area networks; ARMA models; Jacobson´s algorithm; Poisson distribution; WAN; autoregressive moving average models; delay sequences; delay-boundary prediction algorithms; deviation-lag function; end-to-end delay variations; fractal-like structure; jitter deviation; jitter-based delay-boundary prediction; lowpass filters; prediction error rate reduction; robust high-order statistical information; skeleton implementation model; transport protocols; wide-area networks; Delay; Error analysis; Filters; Fractals; Jacobian matrices; Jitter; Prediction algorithms; Predictive models; Robustness; Transport protocols;
Journal_Title :
Networking, IEEE/ACM Transactions on