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

  • Authors:
  • P. L. Conti;L. De Giovanni;M. Naldi

  • Affiliations:
  • Universitá di Roma "La Sapienza", Dipartimento di Statistica, Probabilitá e Statistiche Applicate, Piazzale Aldo Moro, Rome, Italy;Universitá LUMSA, Piazza delle Vaschette 101, 00193 Rome, Italy;Universitá di Roma "Tor Vergata", Dipartimento di Informatica, Sistemi e Produzione, Via del Politecnico 1, Rome, Italy

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2010

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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.