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Blind Network Tomography

dc.contributor.authorRaza, Muhammad
dc.contributor.copyright-releaseNot Applicableen_US
dc.contributor.degreeDoctor of Philosophyen_US
dc.contributor.departmentDepartment of Engineering Mathematicsen_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.external-examinerDr. Dimitrios Hatzinakosen_US
dc.contributor.graduate-coordinatorDr. Guy C. Kemberen_US
dc.contributor.manuscriptsNot Applicableen_US
dc.contributor.thesis-readerDr. Serguei Iakovlev, Dr. Srinivas Sampallien_US
dc.contributor.thesis-supervisorDr. William J. Phillips, Dr. Bill Robertson, Dr. JaceK Ilowen_US
dc.date.accessioned2011-08-17T14:02:40Z
dc.date.available2011-08-17T14:02:40Z
dc.date.defence2011-07-18
dc.date.issued2011-08-17
dc.description.abstractabstract The parameters required for network monitoring are not directly measurable and could be estimated indirectly by network tomography. Some important research issues, related to network tomography, motivated the research in this dissertation. The research work in this dissertation makes four significant novel contributions to the field of network tomography. These research contributions were focused on the blind techniques for performing network tomography, the modeling of errors in network tomography, improving estimates with multi-metric-based network tomography, and distributed network tomography. All of these four research problems, related to network tomography, were solved by various blind techniques including NNMF, SCS, and NTF. These contributions have been verified by processing the data obtained from laboratory experiments and by examining the correlation between the estimated and measured link delays. Evaluation of these contributions was based on the data obtained from various test beds that consisted of networking devices.en_US
dc.identifier.urihttp://hdl.handle.net/10222/14074
dc.subjectTraffic Monitoring, Traffic Analysis, Error Modeling, NNMF, Multi-metric Network Tomographyen_US
dc.titleBlind Network Tomographyen_US

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