Evaluating the limits of network topology inference via virtualized network emulation

Approved for public release; distribution is unlimited === The 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 th...

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Main Author: Rye, Erik C.
Other Authors: Beverly, Robert
Published: Monterey, California: Naval Postgraduate School 2015
Online Access:http://hdl.handle.net/10945/45932
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spelling ndltd-nps.edu-oai-calhoun.nps.edu-10945-459322015-08-07T04:15:11Z Evaluating the limits of network topology inference via virtualized network emulation Rye, Erik C. Beverly, Robert Gera, Ralucca Rohrer, Justin Computer Science Applied Mathematics Approved for public release; distribution is unlimited The 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. 2015-08-05T23:06:01Z 2015-08-05T23:06:01Z 2015-06 Thesis http://hdl.handle.net/10945/45932 This 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. Monterey, California: Naval Postgraduate School
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description Approved for public release; distribution is unlimited === The 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.
author2 Beverly, Robert
author_facet Beverly, Robert
Rye, Erik C.
author Rye, Erik C.
spellingShingle Rye, Erik C.
Evaluating the limits of network topology inference via virtualized network emulation
author_sort Rye, Erik C.
title Evaluating the limits of network topology inference via virtualized network emulation
title_short Evaluating the limits of network topology inference via virtualized network emulation
title_full Evaluating the limits of network topology inference via virtualized network emulation
title_fullStr Evaluating the limits of network topology inference via virtualized network emulation
title_full_unstemmed Evaluating the limits of network topology inference via virtualized network emulation
title_sort evaluating the limits of network topology inference via virtualized network emulation
publisher Monterey, California: Naval Postgraduate School
publishDate 2015
url http://hdl.handle.net/10945/45932
work_keys_str_mv AT ryeerikc evaluatingthelimitsofnetworktopologyinferenceviavirtualizednetworkemulation
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