Academic Journal

Analysis of Graph Layout Algorithms for Use in Command and Control Network Graphs

Bibliographic Details
Title: Analysis of Graph Layout Algorithms for Use in Command and Control Network Graphs
Authors: Stone, Matthew R.
Source: Theses and Dissertations
Publisher Information: AFIT Scholar
Publication Year: 2022
Collection: AFTI Scholar (Air Force Institute of Technology)
Subject Terms: GraphViz, Visualizations, Command and control, Graphics and Human Computer Interfaces
Description: This research is intended to determine which styles of layout algorithm are well suited to Command and Control (C2) network graphs to replace current manual layout methods. Manual methods are time intensive and an automated layout algorithm should decrease the time spent creating network graphs. Simulations on realistic synthetically generated graphs provide information to help infer which algorithms perform better than others on this problem. Data is generated using statistics drawn from multiple real world C2 network graphs. The three algorithms tested against this data are the Spectral algorithm, the Dot algorithm, and the Fruchterman-Reingold algorithm. The results include a multiple objective statistics designed to inform on the algorithms performance in both aesthetic characteristics defined in literature, as well as some characteristics defined by the research sponsor. The results suggest that the Dot algorithm performs better with respect to the sponsor defined characteristics, whereas the Fruchterman-Reingold algorithm performs better on aesthetic characteristics.
Document Type: text
File Description: application/pdf
Language: unknown
Relation: https://scholar.afit.edu/etd/5546; https://scholar.afit.edu/context/etd/article/6548/viewcontent/AD1181199.pdf
Availability: https://scholar.afit.edu/etd/5546
https://scholar.afit.edu/context/etd/article/6548/viewcontent/AD1181199.pdf
Accession Number: edsbas.89BA75D6
Database: BASE
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  Data: Analysis of Graph Layout Algorithms for Use in Command and Control Network Graphs
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  Data: <searchLink fieldCode="AR" term="%22Stone%2C+Matthew+R%2E%22">Stone, Matthew R.</searchLink>
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  Data: Theses and Dissertations
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  Data: AFIT Scholar
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  Data: 2022
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  Data: AFTI Scholar (Air Force Institute of Technology)
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  Data: <searchLink fieldCode="DE" term="%22GraphViz%22">GraphViz</searchLink><br /><searchLink fieldCode="DE" term="%22Visualizations%22">Visualizations</searchLink><br /><searchLink fieldCode="DE" term="%22Command+and+control%22">Command and control</searchLink><br /><searchLink fieldCode="DE" term="%22Graphics+and+Human+Computer+Interfaces%22">Graphics and Human Computer Interfaces</searchLink>
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  Label: Description
  Group: Ab
  Data: This research is intended to determine which styles of layout algorithm are well suited to Command and Control (C2) network graphs to replace current manual layout methods. Manual methods are time intensive and an automated layout algorithm should decrease the time spent creating network graphs. Simulations on realistic synthetically generated graphs provide information to help infer which algorithms perform better than others on this problem. Data is generated using statistics drawn from multiple real world C2 network graphs. The three algorithms tested against this data are the Spectral algorithm, the Dot algorithm, and the Fruchterman-Reingold algorithm. The results include a multiple objective statistics designed to inform on the algorithms performance in both aesthetic characteristics defined in literature, as well as some characteristics defined by the research sponsor. The results suggest that the Dot algorithm performs better with respect to the sponsor defined characteristics, whereas the Fruchterman-Reingold algorithm performs better on aesthetic characteristics.
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      – Text: unknown
    Subjects:
      – SubjectFull: GraphViz
        Type: general
      – SubjectFull: Visualizations
        Type: general
      – SubjectFull: Command and control
        Type: general
      – SubjectFull: Graphics and Human Computer Interfaces
        Type: general
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      – TitleFull: Analysis of Graph Layout Algorithms for Use in Command and Control Network Graphs
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            NameFull: Stone, Matthew R.
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          Dates:
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              M: 01
              Type: published
              Y: 2022
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