Temporal Dependence Network Link Loss Inference from Unicast End-to-End Measurements

Gaolei FEI  Guangmin HU  

IEICE TRANSACTIONS on Communications   Vol.E95-B   No.6   pp.1974-1977
Publication Date: 2012/06/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.E95.B.1974
Print ISSN: 0916-8516
Type of Manuscript: Special Section LETTER (Special Section on Towards Management for Future Networks and Services)
k-th order Markov chain,  temporal dependence,  link loss,  end-to-end measurement,  network tomography,  

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In this letter, we address the issue of estimating the temporal dependence characteristic of link loss by using network tomography. We use a k-th order Markov chain (k > 1) to model the packet loss process, and estimate the state transition probabilities of the link loss model using a constrained optimization-based method. Analytical and simulation results indicate that our method yields more accurate packet loss probability estimates than existing loss inference methods.