Predicting Internet end-to-end delay: a multiple-model approach

This paper presents a novel approach to predict the Internet end-to-end delay using multiple-model (MM) methods. The basic idea of the MM method is to assume the system dynamics can be described by a set of models rather than a single one; by running a bank of filters (each corresponds to a certain...

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Bibliographic Details
Main Authors: Yang, M., Ru, J., Li, X.R., Chen, H., Bashi, A.
Format: Conference Proceeding
Language:English
Subjects:
Data analysis
Delay effects
Filter bank
Information filtering
Information filters
Internet
Predictive models
Time measurement
Time series analysis
Vector quantization
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Summary:This paper presents a novel approach to predict the Internet end-to-end delay using multiple-model (MM) methods. The basic idea of the MM method is to assume the system dynamics can be described by a set of models rather than a single one; by running a bank of filters (each corresponds to a certain model in the set) in parallel at the same time, the MM output is given by a combination of the estimates from these filters. Based on collected end-to-end delay data and preliminary data analysis, we propose an off-line model set design procedure using vector quantization (VQ) and short-term time series analysis so that MM methods can be applied to predict on-line measurement data. Numerical results show that the proposed MM predictor outperforms two widely used adaptive filters in terms of prediction accuracy and robustness.
ISSN:0743-166X
2641-9874
DOI:10.1109/INFCOM.2005.1498568