Blind maximum likelihood estimation of traffic matrices under long-range dependent traffic |
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| Authors: | PL Conti L De Giovanni M Naldi |
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| Affiliation: | 1. Universitá di Roma “La Sapienza”, Dipartimento di Statistica, Probabilitá e Statistiche Applicate, Piazzale Aldo Moro, Rome, Italy;2. Universitá LUMSA, Piazza delle Vaschette 101, 00193 Rome, Italy;3. Universitá di Roma “Tor Vergata”, Dipartimento di Informatica, Sistemi e Produzione, Via del Politecnico 1, Rome, Italy;1. National Key Laboratory of Science and Technology on Multispectral Information Processing, School of Automation, Huazhong University of Science and Technology, Wuhan 430074, Hubei, PR China;2. Department of Chemical Engineering, National Tsing-Hua University, Hsin Chu, Taiwan;3. School of Mechanical & Electrical Engineering, Wuhan Institute of Technology, Wuhan, PR China |
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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. |
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