Location of Things (LoT): A review and taxonomy of sensors localization in IoT infrastructure

Rathin Chandra Shit, Suraj Sharma, Deepak Puthal, Albert Y. Zomaya

Research output: Contribution to journalArticlepeer-review

164 Scopus citations

Abstract

Internet of Things (IoT) is a novel design paradigm, intended as a network of billions to trillions of tiny sensors communicating with each other to offer innovative solutions to real time problems. These sensors form a network named as wireless sensor networks (WSNs) to monitor physical environment and disseminate collected data back to the base station through multiple hops. WSN has the capability to collect and report data for a specific application. The location information plays an important role for various wireless sensor network applications. A majority of the applications are related to location-based services. The development of sensor technology, processing techniques, and communication systems give rise to a development of the smart sensor for the adaptive and innovative application. So a single localization technique is not adequate for all application. In this paper, a recent extensive analysis of localization techniques and hierarchical taxonomy and their applications in the different context is presented. This taxonomy of the localization technique is classified based on presence of offline training in localization, namely self-determining and training dependent approaches. Finally, various open research issues related to localization schemes for IoT are compared and various directions for future research are proposed.

Original languageBritish English
Article number8270611
Pages (from-to)2028-2061
Number of pages34
JournalIEEE Communications Surveys and Tutorials
Volume20
Issue number3
DOIs
StatePublished - 1 Jul 2018

Keywords

  • finger-printing
  • Internet of Things (IoT)
  • LMFF
  • localization
  • MDS
  • RBFM
  • SDP
  • Wireless sensor network (WSN)

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