NDLI: Temporal dependence network loss tomography using maximum pseudo likelihood method

Content Provider	IEEE Xplore Digital Library
Author	Gaolei Fei Guangmin Hu
Copyright Year	2012
Description	Author affiliation: Key Laboratory of Optical Fiber Sensing & Communication, Ministry of Education, University of Electronic Science and Technology of China (Gaolei Fei; Guangmin Hu)
Abstract	Understanding network link loss is particularly important for optimizing delay-sensitive applications. This paper addresses the problem of estimating temporal dependence characteristic of link loss by using network tomography. First, the k-th order Markov Chain (k > 1) is introduced to model the packet loss process. The model considers the dependence of k + 1 consecutive packets, and is capable of capturing the temporal dependence characteristic of link loss accurately if k is large enough. Second, we propose a maximum pseudo likelihood inference based method to estimate the state transition probabilities of the k-th order Markov Chain link loss model from the unicast end-to-end measurements. The analytical and simulation results show the good performance of our method.
Starting Page	545
Ending Page	550
File Size	491624
Page Count	6
File Format	PDF
ISBN	9781467302517
ISSN	19767684
e-ISBN	9781467302500
DOI	10.1109/ICOIN.2012.6164437
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-02-01
Publisher Place	Indonesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Probes Loss measurement Unicast Tomography Indexes Joints Mathematical model
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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