Distributed fault-tolerant classification in wireless sensor networks

Tsang Yi Wang, Yunghsiang S. Han, Pramod K. Varshney, Po Ning Chen

Research output: Contribution to journalArticlepeer-review

87 Scopus citations


Fault-tolerance and data fusion have been considered as two fundamental functions in wireless sensor networks. In this paper, we propose a novel approach for distributed multiclass classification using a fault-tolerant fusion rule for wireless sensor networks. Binary decisions from local sensors, possibly in the presence of faults, are forwarded to the fusion center that determines the final classification result. Classification fusion in our approach is implemented via error correcting codes to incorporate fault-tolerance capability. This new approach not only provides an improved fault-tolerance capability but also reduces computation time and memory requirements at the fusion center. Code matrix design is essential for the design of such systems. Two efficient code matrix design algorithms are proposed in this paper. The relative merits of both algorithms are also studied. We also develop sufficient conditions for asymptotic detection of the correct hypothesis by the proposed approach. Performance evaluation of the proposed approach in the presence of faults is provided. These results show significant improvement in fault-tolerance capability as compared with conventional parallel fusion networks.

Original languageEnglish (US)
Pages (from-to)724-733
Number of pages10
JournalIEEE Journal on Selected Areas in Communications
Issue number4
StatePublished - Apr 2005


  • Data fusion
  • Decision fusion
  • Distributed classification
  • Error correcting codes
  • Fault-tolerance
  • Multisensor systems
  • Wireless sensor networks (WSNs)

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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