An Algorithm for Classifying PSTN Switching Stations.

Abstract

The National Security Agency (NSA) collects and processes signals intelligence information for national security purposes. As part of this mission, NSA predicts message routing over public switched telephone networks (PSTNs). The hierarchical switching level (or classification) of PSTN switching stations must be determined before making routing predictions. This thesis develops a fast graph-theoretic algorithm for accomplishing this classification. An undirected connected graph models a target PSTN; switching stations are nodes and logical connections between the switching stations are unit-length arcs. We develop bounds for the minimum number of switching levels and implicitly enumerate all possible classifications for each PS TN. The algorithm is implemented in Java and PSTNs are classified using a personal computer. Solutions are obtained in under one second for nine real-world PSTNs, and large notional networks of over 300 nodes and 900 arcs are classified in under one minute. This research improves existing node classification software.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1998
Accession Number
ADA355957

Entities

People

  • John F. Brandeau

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Classification
  • Computer Programming
  • Computer Programs
  • Computers
  • Engineering
  • Language
  • Linear Programming
  • National Security
  • Network Science
  • Operations Research
  • Personal Computers
  • Signals Intelligence
  • United States
  • United States Government

Fields of Study

  • Computer science

Readers

  • Cybersecurity.
  • Graph Algorithms and Convex Optimization.
  • Neural Network Machine Learning.