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dc.contributor.advisorBeverly, Robert
dc.contributor.advisorGera, Ralucca
dc.contributor.authorRye, Erik C.
dc.dateJun-15
dc.date.accessioned2015-08-05T23:06:01Z
dc.date.available2015-08-05T23:06:01Z
dc.date.issued2015-06
dc.identifier.urihttp://hdl.handle.net/10945/45932
dc.descriptionApproved for public release; distribution is unlimiteden_US
dc.description.abstractThe Internet measurement community is beset by a lack of ground truth, or knowledge of the real, underlying network in topology inference experiments. While better tools and methodologies can be developed, quantifying the effectiveness of these mapping utilities and explaining pathologies is difficult, if not impossible, without knowing the network topology being probed. In this thesis we present a tool that eliminates topological uncertainty in an emulated, virtualized environment. First, we automatically build topological ground truth according to various network generation models and create emulated Cisco router networks by leveraging and modifying existing emulation software. We then automate topological inference from one vantage point at a time for every vantage point in the network. Finally, we incorporate a mechanism to study common sources of network topology inference abnormalities by including the ability to induce link failures within the network. In addition, this thesis reexamines previous work in sampling Autonomous System-level Internet graphs to procure realistic models for emulation and simulation. We build upon this work by including additional data sets, and more recent Internet topologies to sample from, and observe divergent results from the authors of the original work. Lastly, we introduce a new technique for sampling Internet graphs that better retains particular graph metrics across multiple timeframes and data sets.en_US
dc.description.urihttp://archive.org/details/evaluatinglimits1094545932
dc.publisherMonterey, California: Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleEvaluating the limits of network topology inference via virtualized network emulationen_US
dc.typeThesisen_US
dc.contributor.secondreaderRohrer, Justin
dc.contributor.departmentComputer Science
dc.contributor.departmentApplied Mathematics
dc.contributor.departmentComputer Scienceen_US
dc.contributor.departmentApplied Mathematicsen_US
dc.subject.authorNetwork Emulationen_US
dc.subject.authorGraph Samplingen_US
dc.subject.authorTopology Inferenceen_US
dc.subject.authorNetwork Measurementen_US
dc.description.recognitionOutstanding Thesisen_US
dc.description.recognitionOutstanding Thesisen_US
dc.description.serviceCaptain, United States Marine Corpsen_US
etd.thesisdegree.nameMaster of Science in Computer Science and Master of Science in Applied Mathematicsen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineComputer Science and Applied Mathematicsen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US


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