Range-Free Localization Schemes for Large Scale Sensor Networks

Abstract

Wireless Sensor Networks have been proposed for a multitude of location-dependent applications. For such systems, the cost and limitations of hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute point-to-point distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. In this paper, we present APIT, a novel localization algorithm that is range-free. We show that our APIT scheme performs best when an irregular radio pattern and random node placement are considered, and low communication overhead is desired. We compare our work via extensive simulation, with three state-of-the-art range-free localization schemes to identify the preferable system configurations of each. In addition, we study the effect of location error on routing and tracking performance. We show that routing performance and tracking accuracy are not significantly affected by localization error when the error is less than 0.4 times the communication radio radius.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2003
Accession Number
ADA436740

Entities

People

  • Brain M. Blum
  • Chengdu Huang
  • John A. Stankovic
  • Tarek Abdelzaher
  • Tian He

Organizations

  • University of Virginia

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Angle Of Arrival
  • Center Of Gravity
  • Computational Complexity
  • Computer Science
  • Deployment
  • Detectors
  • Electromagnetic Wave Propagation
  • Errors
  • Heterogeneous Networks
  • Mesh Networks
  • Networks
  • Sensor Networks
  • Simulations
  • Test And Evaluation
  • Wireless Sensor Networks

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Networking