A new method, based on the maximum likelihood principle, through the numerical Expectation–Maximization algorithm, is proposed to estimate traffic matrices when traffic exhibits long-range dependence. The methods proposed so far in the literature do not account for long-range dependence. The method proposed in the present paper also provides an estimate of the Hurst parameter. Simulation results show that: (i) the estimate of the traffic matrix is more efficient than those obtained via existing techniques; (ii) the estimation error of the traffic matrix is lower for larger values of the true traffic intensity; (iii) the estimate of the Hurst parameter is slightly negatively biased. Keywords. Traffic matrices, Long-range dependence, Traffic matrix estimation

Blind Maximum Likelihood Estimation of Traffic Matrices under Long Range Dependent Traffic / Conti, P. L; DE GIOVANNI, Livia; Naldi, M.. - In: COMPUTER NETWORKS. - ISSN 1389-1286. - 54:15(2010), pp. 2626-2639. [10.1016/j.comnet.2010.04.012]

Blind Maximum Likelihood Estimation of Traffic Matrices under Long Range Dependent Traffic

DE GIOVANNI, LIVIA;
2010

Abstract

A new method, based on the maximum likelihood principle, through the numerical Expectation–Maximization algorithm, is proposed to estimate traffic matrices when traffic exhibits long-range dependence. The methods proposed so far in the literature do not account for long-range dependence. The method proposed in the present paper also provides an estimate of the Hurst parameter. Simulation results show that: (i) the estimate of the traffic matrix is more efficient than those obtained via existing techniques; (ii) the estimation error of the traffic matrix is lower for larger values of the true traffic intensity; (iii) the estimate of the Hurst parameter is slightly negatively biased. Keywords. Traffic matrices, Long-range dependence, Traffic matrix estimation
Traffic matrices; Long-range dependence; Traffic matrix estimation
Blind Maximum Likelihood Estimation of Traffic Matrices under Long Range Dependent Traffic / Conti, P. L; DE GIOVANNI, Livia; Naldi, M.. - In: COMPUTER NETWORKS. - ISSN 1389-1286. - 54:15(2010), pp. 2626-2639. [10.1016/j.comnet.2010.04.012]
File in questo prodotto:
File Dimensione Formato  
abstractCN2010.pdf

Solo gestori archivio

Tipologia: Abstract
Licenza: DRM non definito
Dimensione 61.88 kB
Formato Adobe PDF
61.88 kB Adobe PDF   Visualizza/Apri
COMPNW4233.pdf

Solo gestori archivio

Tipologia: Documento in Post-print
Licenza: DRM non definito
Dimensione 640.24 kB
Formato Adobe PDF
640.24 kB Adobe PDF   Visualizza/Apri
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11385/6042
Citazioni
  • Scopus 17
  • ???jsp.display-item.citation.isi??? 16
social impact