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. (C) 2010 Elsevier B.V. All rights reserved.
Blind maximum likelihood estimation of traffic matrices under long-range dependent traffic / Conti, Pier Luigi; L., De Giovanni; M., Naldi. - In: COMPUTER NETWORKS. - ISSN 1389-1286. - STAMPA. - 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
CONTI, Pier Luigi;
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. (C) 2010 Elsevier B.V. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
