Evaluation of Energy Costs and Error Performance of Range-Aware Anchor-Free Localization Algorithms for Wireless Sensor Networks

Abstract

This research examines energy and error tradeoffs in Anchor-Free Range-Aware Wireless Sensor Network (WSN) Localization algorithms. A concurrent and an incremental algorithm (Anchor Free Localization (AFL) and Map Growing) are examined under varying network sizes, densities, deployments, and range errors. Despite current expectations, even the most expensive configurations do not expend significant battery life (at most 0.4%), implying little energy can be conserved during localization. Due to refinement, AFL is twice as accurate, using 6 times the communication. For both, node degree affects communication most. As degree increases, Map Growing communication increases, while AFL transmissions drop. Nodes with more neighbors refine quicker with fewer messages. At high degree, many nodes receive the same message, overpowering the previous effect, and raising AFL received bits. Built from simulation data, the Energy Consumption Model predicts energy usage of incremental and concurrent algorithms used in networks with varying size, density, and deployments. It is applied to current wireless sensor nodes. Military WSNs should be flexible, cheap, and long lasting. Anchor-Free, Range-Aware algorithms best fit this need.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2006
Accession Number
ADA447060

Entities

People

  • Gustav J. Jordt

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Ad Hoc Networks
  • Air Force
  • Angle Of Arrival
  • Computer Networks
  • Coordinate Systems
  • Detection
  • Detectors
  • Energy Conservation
  • Energy Consumption
  • Global Positioning Systems
  • Intrusion Detection
  • Mesh Networks
  • Range Finding
  • Sensor Networks
  • Two Dimensional
  • Wireless Communications
  • Wireless Sensor Networks

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Mathematical Modeling and Probability Theory.
  • Mathematics or Statistics