Location Information-Aided Task-Oriented Self-Organization of Ad-Hoc Sensor Systems

Kamal Premaratne, Jinsong Zhang, Mural Doǧruel

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


A novel task-oriented self-organization algorithm that accounts for mostly location-dependent tasks and heterogeneous sensors inherent in dense ad-hoc sensor systems is proposed. It forms a sensor group for an announced task by sequentially selecting the best matched sensors using a leader election algorithm and a residual task calculation algorithm. To improve the associated communication overhead, the sensor node location information is used in task broadcasting, thus confining the algorithm implementation to a dynamically maintained contributor group which comprises of those sensors which may contribute to the task. Sensor localization is based on a refinement of an algorithm in [1] which utilizes only the neighborhood information of each sensor node corresponding to its each preset radio transmission power level. The proposed self-organization algorithm and how various system parameters affect its performance are examined via extensive simulations. In a densely deployed sensor system, when the refined localization scheme is demonstrated to achieve very good localization, the proposed self-organization algorithm consistently yields a sensor group that covers the announced task.

Original languageEnglish (US)
Pages (from-to)85-95
Number of pages11
JournalIEEE Sensors Journal
Issue number1
StatePublished - Feb 2004


  • Ad-hoc sensor systems
  • Localization
  • Self-organization
  • Sensor selection

ASJC Scopus subject areas

  • Engineering(all)
  • Electrical and Electronic Engineering


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