Network of TAMCNS: Identifying Influence Regions Within the GCSS-MC Database

Abstract

The Global Combat Support System-Marine Corps (GCSS-MC) system enables the logistics and supply chain management systemfor the United States Marine Corps. This system allows leaders, operators, maintainers, and suppliers to work together on a commonplatform and provides transparency and situational awareness in the logistics and supply cycle. The data associated with the GCSS-MCsystem is stored in a database. As the size of the data increases, challenges arise in obtaining insights into large data sets and its impacton network infrastructure. Network science identifies relationships between objects and provides tools to quantitatively determineobjects whose influence impacts other objects or the system as a whole. This thesis applies network science techniques to determineimportant Table of Authorized Material Control Numbers (TAMCNs) in the GCSS-MC database, according to their impact on otherTAMCNs in the database based on degree, eigenvector, betweenness, and closeness centrality. Additionally, this thesis developsa formula to rank components from most to least important. We further develop a process to identify pertinent tables within thedatabase and export the information to create a complex network containing multiple layers that analyze various attributes associatedwith GCSS-MC. We find that the methodology identifies the most important TAMCN and provides a list of TAMCNs in order ofimportance. We also analyze the community and core structure of the GCSS-MC complex network and identify influential TAMCNregions in the database.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2017
Accession Number
AD1046313

Entities

People

  • Victor G. Castro

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Computer Programming
  • Computer Science
  • Computers
  • Data Analysis
  • Databases
  • Domain Specific Programming Languages
  • Graph Theory
  • Graphical User Interface
  • Html
  • Infrastructure
  • Light Armored Vehicles
  • Load Monitoring
  • Logistics
  • Mobile Ad Hoc Networks
  • Network Science
  • Social Networks
  • United States

Fields of Study

  • Computer science

Readers

  • Data Mining and Knowledge Discovery.
  • Military Leadership and Professional Education.
  • Neural Network Machine Learning.