Accurate 3-D Localization of Selected Smart Objects in Optical Internet of Underwater Things

Nasir Saeed*, Mohamed Slim Alouini, Tareq Y. Al-Naffouri

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

Localization is a fundamental task for the optical Internet of Underwater Things (O-IoUT) to enable various applications, such as data tagging, routing, navigation, and maintaining link connectivity. The accuracy of the localization techniques for O-IoUT greatly relies on the location of the anchors. Therefore, recently, the localization techniques for O-IoUT which optimize the anchor's location have been proposed. However, the optimization of the anchors' location for all the smart objects in the network is not a useful solution. Indeed, in a network of densely populated smart objects, the data collected by some sensors are more valuable than the data collected from other sensors. Therefore, in this article, we propose a 3-D accurate localization technique by optimizing the anchor's location for a set of smart objects. Spectral graph partitioning is used to select the set of valuable sensors. The numerical results show that the proposed technique of optimizing anchor's location for a set of selected sensors provides a better location accuracy.

Original languageEnglish (US)
Article number8862956
Pages (from-to)937-947
Number of pages11
JournalIEEE Internet of Things Journal
Volume7
Issue number2
DOIs
StatePublished - Feb 2020

Keywords

  • Anchor's location
  • data tagging
  • localization
  • optical Internet of Underwater Things (O-IoUT)
  • routing

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

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