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, previous studies have revealed a fractal-like structure of delay sequences, which may not be well suited to ARMA models. We pro...
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Published in | IEEE/ACM transactions on networking Vol. 9; no. 5; pp. 578 - 590 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.10.2001
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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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. |
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AbstractList | 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. 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 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. |
Author | Mills, D.L. Qiong Li |
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Cites_doi | 10.1109/ICC.1997.605360 10.1007/978-3-642-95281-4 10.1109/90.664264 10.1109/90.554723 10.1145/52325.52356 10.1109/90.664263 10.1145/316194.316230 10.1007/978-1-4899-2124-6 10.1145/118544.118549 10.1145/316194.316220 10.1145/285243.285256 10.1109/GLOCOM.1999.832481 |
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References | ref12 Bertsekas (ref3) 1992 ref10 Ljung (ref13) 1987 ref2 ref1 Li (ref11) 2000 ref17 ref16 ref8 Cohen (ref5) 1976 ref7 Meakin (ref14) 1998 ref9 ref4 Postel (ref15) 1981; RFC-793 ref6 |
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SubjectTerms | Algorithms Delay Deviation Error analysis Feasibility Filters Fractals Jacobian matrices Jitter Joints Mathematical models Prediction algorithms Predictive models Robustness Transport Transport protocols |
Title | Jitter-based delay-boundary prediction of wide-area networks |
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