Probabilistic assessment of high-throughput wireless sensor networks

Robin E. Kim, Kirill Mechitov, Sung Han Sim, Billie F. Spencer, Junho Song

Research output: Contribution to journalArticle

Abstract

Structural health monitoring (SHM) using wireless smart sensors (WSS) has the potential to provide rich information on the state of a structure. However, because of their distributed nature, maintaining highly robust and reliable networks can be challenging. Assessing WSS network communication quality before and after finalizing a deployment is critical to achieve a successful WSS network for SHM purposes. Early studies on WSS network reliability mostly used temporal signal indicators, composed of a smaller number of packets, to assess the network reliability. However, because the WSS networks for SHM purpose often require high data throughput, i.e., a larger number of packets are delivered within the communication, such an approach is not sufficient. Instead, in this study, a model that can assess, probabilistically, the long-term performance of the network is proposed. The proposed model is based on readily-available measured data sets that represent communication quality during high-throughput data transfer. Then, an empirical limit-state function is determined, which is further used to estimate the probability of network communication failure. Monte Carlo simulation is adopted in this paper and applied to a small and a full-bridge wireless networks. By performing the proposed analysis in complex sensor networks, an optimized sensor topology can be achieved.

Original languageEnglish (US)
Article number792
JournalSensors (Switzerland)
Volume16
Issue number6
DOIs
StatePublished - Jun 2016

Keywords

  • High-throughput data transfer
  • Network communication reliability
  • Probabilistic assessment
  • Structural health monitoring
  • Wireless sensor networks

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

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