Unifying unknown nodes in the internet graph using semisupervised spectral clustering

Anat Almog, J. Goldberger, Yuval Shavitt

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Most research on Internet topology is based on active measurement methods. A major difficulty in using these tools is that one comes across many unresponsive routers. Different methods of dealing with these anonymous nodes to preserve the connectivity of the real graph have been suggested. One of the more practical approaches involves using a placeholder for each unknown, resulting in multiple copies of every such node. This significantly distorts and inflates the inferred topology. Our goal in this work is to unify groups of placeholders in the IP-level graph. We introduce a novel clustering algorithm based on semisupervised spectral embedding of all the nodes followed by clustering of the anonymous nodes in the projected space. Experimental results on real internet data are provided, that show good similarity to the true networks.
Original languageAmerican English
Title of host publication2008 IEEE International Conference on Data Mining Workshops
StatePublished - 2008

Bibliographical note

Place of conference:Italy


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