Heuristically Driven Search Methods for Topology Control in Directional Wireless Hybrid Networks

Abstract

Information and Networked Communications play a vital role in the everyday operations of the United States Armed Forces. This research establishes a comparative analysis of the unique network characteristics and requirements introduced by the Topology Control Problem (also known as the Network Design Problem). Previous research has focused on the development of Mixed-Integer Linear Program (MILP) formulations, simple heuristics, and Genetic Algorithm (GA) strategies for solving this problem. Principal concerns with these techniques include runtime and solution quality. To reduce runtime, new strategies have been developed based on the concept of flow networks using the novel combination of three well-known algorithms; knapsack, greedy commodity filtering, and maximum flow. The performance of this approach and variants are compared with previous research using several network metrics including computation time, cost, network diameter, dropped commodities, and average number of hops per commodity. The results conclude that maximum flow algorithms alone are not quite as effective as previous findings, but are at least comparable and show potential for larger networks.v

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2007
Accession Number
ADA469317

Entities

People

  • Roger L. Garner

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Algorithms
  • Computational Complexity
  • Computers
  • Department Of Defense
  • Evolutionary Algorithms
  • Experimental Design
  • Flow Network
  • Genetic Algorithms
  • Heuristic Methods
  • Information Operations
  • Linear Programming
  • Military Operations
  • Network Topology
  • United States
  • Unmanned Aerial Vehicles

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Operations Research
  • Strategic Security Studies

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks
  • Biotechnology