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Impact of duty cycle and radio range irregularity on localization algorithms for wireless sensor networks

  • Dalian University of Technology

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

In this paper, we investigate the performance of Hop-based localization algorithms in time-varying and direction-varying connectivity (TDVC) wireless sensor network under various parameter configurations. In real scenario, TDVC is a common phenomenon which arises from the node's duty cycle for saving energy and radio range irregularity of sensor node due to multiple factors, such as variance in radio frequency, sending power and different packet loss probabilities, depending on the direction of propagation. With empirical data obtained from Tmote Sky/TelosB platform, we establish a TDVC network model for simulation, called Time and Direction Connectivity Variation Model (TDCVM). This model is the first to bridge the discrepancy between ideal connectivity models used by some previous literatures and the practical connectivity between nodes of network. With this model, we do extensive experiments using three Hop-based localization methods (DV-Hop, HCRL and REP) to analyze the impact of parameters, i.e., k, degree of irregularity (DOI), anchor node density, and the number of nodes of a network on localization accuracy. Our results show that these parameters are interactional and different parameter configurations have different localization errors. Furthermore, these experimental results can be used to direct the design of dynamic (the "dynamic" results from duty-cycling) algorithms under more realistic environment and achieve high localization accuracy. To the best of our knowledge, our insight is the only performance exploration for range-free localization algorithms with duty-cycled and radio-range-irregular sensor nodes.

Original languageEnglish
Pages (from-to)219-235
Number of pages17
JournalAd-Hoc and Sensor Wireless Networks
Volume21
Issue number3-4
StatePublished - 2014

Keywords

  • Connected k-neighborhood
  • Duty cycle
  • Dynamic network
  • Localization algorithm
  • Radio range irregularity
  • Wireless sensor networks

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