Title
Improving maximum-likelihood-based topology inference by sequentially inserting leaf nodes.
Abstract
Understanding the topology of a network is very important for network control and management. There have been several methods designed for estimating network topology from end-to-end measurements. Among these methods, the maximum-likelihood-based topology inference method is superior to suboptimal and pair-merging approaches, because it is capable of finding the global optimal topology. However, t...
Year
DOI
Venue
2011
10.1049/iet-com.2010.0455
IET Communications
Keywords
Field
DocType
maximum likelihood estimation,radio networks,radiofrequency interference,telecommunication network management,telecommunication network topology,trees (mathematics)
Mathematical optimization,Computer network,Binary tree,Maximum likelihood,Algorithm,Network topology,Hypertree network,Network control,Network management,Mathematics,Topology inference
Journal
Volume
Issue
ISSN
5
15
1751-8628
Citations 
PageRank 
References 
1
0.40
13
Authors
2
Name
Order
Citations
PageRank
Gaolei Fei133.14
Guang-min Hu28719.78