Fast optimization method: an on-line hurst parameter estimator

An extended version of optimization method (OM) for on-line Hurst estimation is presented named as fast optimization method (FOM). The on-line Hurst estimator is crucial to characterize self-similar feature on stochastic process and widely applied in various fields such as in network traffic analysi...

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Main Authors: Idris, Mohd. Yazid, Abdullah, Abdul Hanan, Maarof, Mohd. Aizaini
Format: Conference or Workshop Item
Published: 2007
Subjects:
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author Idris, Mohd. Yazid
Abdullah, Abdul Hanan
Maarof, Mohd. Aizaini
author_facet Idris, Mohd. Yazid
Abdullah, Abdul Hanan
Maarof, Mohd. Aizaini
author_sort Idris, Mohd. Yazid
collection ePrints
description An extended version of optimization method (OM) for on-line Hurst estimation is presented named as fast optimization method (FOM). The on-line Hurst estimator is crucial to characterize self-similar feature on stochastic process and widely applied in various fields such as in network traffic analysis, bandwidth provisioning and anomaly detection. Recent on-line Hurst estimator based on fast wavelet transform known as real-time wavelet estimator (RWM) is proven can estimates faster than other methods in on-line fashion. However this paper will present the capability of FOM to estimates the Hurst parameter faster than RWM with an acceptable Hurst value, enabling it's to be used in on-line application. In order to verify FOM result and its performance, the method was implemented using two types of self-similar processes that are fractional Gaussian noise (fGn) and MIT/DARPA network traffic data set. The results show a significant improvement on FOM performance compared with RWM. While the estimated Hurst parameter locates in the range of confidence interval of OM method had proven the accuracy of FOM estimation.
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spelling utm.eprints-139772017-08-02T07:57:46Z http://eprints.utm.my/13977/ Fast optimization method: an on-line hurst parameter estimator Idris, Mohd. Yazid Abdullah, Abdul Hanan Maarof, Mohd. Aizaini QA75 Electronic computers. Computer science An extended version of optimization method (OM) for on-line Hurst estimation is presented named as fast optimization method (FOM). The on-line Hurst estimator is crucial to characterize self-similar feature on stochastic process and widely applied in various fields such as in network traffic analysis, bandwidth provisioning and anomaly detection. Recent on-line Hurst estimator based on fast wavelet transform known as real-time wavelet estimator (RWM) is proven can estimates faster than other methods in on-line fashion. However this paper will present the capability of FOM to estimates the Hurst parameter faster than RWM with an acceptable Hurst value, enabling it's to be used in on-line application. In order to verify FOM result and its performance, the method was implemented using two types of self-similar processes that are fractional Gaussian noise (fGn) and MIT/DARPA network traffic data set. The results show a significant improvement on FOM performance compared with RWM. While the estimated Hurst parameter locates in the range of confidence interval of OM method had proven the accuracy of FOM estimation. 2007 Conference or Workshop Item PeerReviewed Idris, Mohd. Yazid and Abdullah, Abdul Hanan and Maarof, Mohd. Aizaini (2007) Fast optimization method: an on-line hurst parameter estimator. In: Postgraduate Annual Research Seminar (PARS’ 07). , 2007, UTM.
spellingShingle QA75 Electronic computers. Computer science
Idris, Mohd. Yazid
Abdullah, Abdul Hanan
Maarof, Mohd. Aizaini
Fast optimization method: an on-line hurst parameter estimator
title Fast optimization method: an on-line hurst parameter estimator
title_full Fast optimization method: an on-line hurst parameter estimator
title_fullStr Fast optimization method: an on-line hurst parameter estimator
title_full_unstemmed Fast optimization method: an on-line hurst parameter estimator
title_short Fast optimization method: an on-line hurst parameter estimator
title_sort fast optimization method an on line hurst parameter estimator
topic QA75 Electronic computers. Computer science
work_keys_str_mv AT idrismohdyazid fastoptimizationmethodanonlinehurstparameterestimator
AT abdullahabdulhanan fastoptimizationmethodanonlinehurstparameterestimator
AT maarofmohdaizaini fastoptimizationmethodanonlinehurstparameterestimator