dc.contributor.authorLuo, Wuqiong
dc.contributor.authorTay, Wee Peng
dc.date.accessioned2013-08-16T04:15:44Z
dc.date.available2013-08-16T04:15:44Z
dc.date.copyright2012en_US
dc.date.issued2012
dc.identifier.urihttp://hdl.handle.net/10220/13163
dc.description.abstractEstimating which nodes are the infection sources that introduce a virus or rumor into a network, or the locations of pollutant sources, plays a critical role in limiting the potential damage to the network through timely quarantine of the sources. In this paper, we derive estimators for the infection sources and their infection regions based on the infection network geometry. We show that in a geometric tree with at most two sources, our estimator identifies these sources with probability going to one as the number of infected nodes increases. We extend and generalize our methods to general graphs, where the number of infection sources are unknown and there may be multiple sources. Numerical results are presented to verify the performance of our proposed algorithms under different types of graph structures.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering
dc.titleIdentifying multiple infection sources in a networken_US
dc.typeConference Paper
dc.contributor.conferenceAsilomar Conference on Signals, Systems and Computers (46th : 2012 : Pacific Grove, USA)en_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1109/ACSSC.2012.6489274


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record