Accuracy-enhanced time synchronization method for WSNs using average consensus control

Ali A. Al-Shaikhi*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Time synchronization in Wireless Sensor Networks (WSNs) is crucial for the proper operation of such networks. The averaging consensus control protocol shows a good time synchronization performance in harsh environments using single hop communication in distributed WSNs. This article presents a modified method, of the averaging consensus algorithm, that further enhances the accuracy of the time synchronization of such networks. The modified method improves time synchronization accuracy at the expense of increased convergence time. However, the former is more important than the latter. The state equation representing the time synchronization error of a node time with respect to the gateway node time has two terms: A natural response and a forced response. The latter was observed that it can be reduced further by introducing a new parameter, a fraction of the time communication rate, in the local time update of each node. As this fraction approaches one, it is observed through simulations and practical experiments that it will lead to orders of magnitude better minimum synchronization error but with an increase in the needed number of communications instances.

Original languageEnglish
Title of host publication2018 15th International Multi-Conference on Systems, Signals and Devices, SSD 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages23-27
Number of pages5
ISBN (Electronic)9781538653050
DOIs
StatePublished - 7 Dec 2018

Publication series

Name2018 15th International Multi-Conference on Systems, Signals and Devices, SSD 2018

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

  • Averaging Protocol
  • Consensus Control
  • Time synchronization
  • Wireless Sensor Networks (WSNs)

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Control and Optimization
  • Instrumentation

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