NDLI: Link Loss Rate Inference Using Success Rate Cumulant Generating Function

Content Provider	IEEE Xplore Digital Library
Author	Chengbo Huang Yongsheng Liang Yilong Xu Guisheng Yi
Copyright Year	2009
Abstract	Inference of the internal link state is an important and challenging issue for operating and evaluating networks. This paper presents a method to infer internal link loss characteristics based on end-to-end measurement. Our method uses cumulant generating function (CGF) inference algorithm. The main contribution of our approach is that we use the success rate CGF instead of the loss rate CGF, because the loss rate CGF cannot be constructed directly. We construct the path success rate CGF first, then the link success rate CGF can be inferred, and the link success rate can be obtained. Employing the relationship between the link loss rate and the link success rate, we can get the link loss rate. The simulation results demonstrate that this method is efficient.
Starting Page	157
Ending Page	160
File Size	159691
Page Count	4
File Format	PDF
ISBN	9780769535678
DOI	10.1109/ICFN.2009.19
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-07
Publisher Place	Thailand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Maximum likelihood estimation loss rate inference Routing Educational institutions Loss measurement Information technology network measurement Tomography Inference algorithms IP networks Communication networks cumulant generating function (CGF) Probes
Content Type	Text
Resource Type	Article

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