Blind maximum likelihood estimation of traffic matrices under long-range dependent traffic

摘要

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.