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Temporal Dependence Network Link Loss Inference from Unicast End-to-End Measurements
Gaolei FEI
Guangmin HU
Publication
IEICE TRANSACTIONS on Communications Vol.E95-B No.6 pp.1974-1977
Publication Date: 2012/06/01
Online ISSN: 1745-1345
Print ISSN: 0916-8516
Type of Manuscript: Special Section LETTER (Special Section on Towards Management for Future Networks and Services)
Category:
Keyword:
k-th order Markov chain,
temporal dependence,
link loss,
end-to-end measurement,
network tomography,
Full Text: PDF(124.5KB)
Summary:
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.
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