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Measuring synchronization precision in mobile sensor networks

Author

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  • F. C. S. Eiras

    (University of São Paulo)

  • W. L. Zucchi

    (University of São Paulo)

Abstract

Many applications involving the use of drones in sensor networks require precise synchronization from the involved sensors. However, not many papers evaluate the precision of the synchronism that can be obtained by means of exchanging packets in mobile sensor networks. This lack can be explained by the difficulties encountered in modeling the swift movements of the drones and the large volumes of these elements in a monitored area. Measuring phase noise also requires techniques that are quite different from those commonly used to analyze data networks. This paper suggests a simulation model based on discrete events, deployed in a Matlab Simulink® tool, which combines calculating loss probability in a mobile sensor network with measuring phase error between the sensor clock and the reference clock. Phase error is evaluated by Maximum Time Interval Error (MTIE) and Allan Deviation (ADEV) statistics. Results show that synchronism precision is strongly connected to the probability of message loss and that, with fewer losses, precision in the order of tens of nano-seconds can be obtained.

Suggested Citation

  • F. C. S. Eiras & W. L. Zucchi, 2022. "Measuring synchronization precision in mobile sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 81(2), pages 253-267, October.
  • Handle: RePEc:spr:telsys:v:81:y:2022:i:2:d:10.1007_s11235-022-00944-9
    DOI: 10.1007/s11235-022-00944-9
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    References listed on IDEAS

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    1. Francisco Tirado-Andrés & Alvaro Araujo, 2019. "Performance of clock sources and their influence on time synchronization in wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 15(9), pages 15501477198, September.
    2. Chakraborty, Suparna & Goyal, N.K. & Mahapatra, S. & Soh, Sieteng, 2020. "A Monte-Carlo Markov chain approach for coverage-area reliability of mobile wireless sensor networks with multistate nodes," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    3. Alexandros Zervopoulos & Athanasios Tsipis & Aikaterini Georgia Alvanou & Konstantinos Bezas & Asterios Papamichail & Spiridon Vergis & Andreana Stylidou & Georgios Tsoumanis & Vasileios Komianos & Ge, 2020. "Wireless Sensor Network Synchronization for Precision Agriculture Applications," Agriculture, MDPI, vol. 10(3), pages 1-20, March.
    4. F. C. S. Eiras & W. L. Zucchi, 2021. "A simulation model for area coverage and loss probability on mobile sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 76(1), pages 3-16, January.
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