Full Text:   <102>

Summary:  <31>

CLC number: TP391; TP393

On-line Access: 2021-01-11

Received: 2020-04-30

Revision Accepted: 2020-08-30

Crosschecked: 2020-12-11

Cited: 0

Clicked: 227

Citations:  Bibtex RefMan EndNote GB/T7714


Rui Wang


Hui Sun


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Frontiers of Information Technology & Electronic Engineering  2021 Vol.22 No.1 P.51-67


Freshness constraints of an age of information based event-triggered Kalman consensus filter algorithm over a wireless sensor network

Author(s):  Rui Wang, Yahui Li, Hui Sun, Youmin Zhang

Affiliation(s):  College of Information Engineering and Automation, Civil Aviation University of China, Tianjin 300300, China; more

Corresponding email(s):   h-sun@cauc.edu.cn

Key Words:  Distributed Kalman consensus filter (KCF), Event-triggered mechanism, Age of information (AoI), Stability analysis, Energy optimization

Rui Wang, Yahui Li, Hui Sun, Youmin Zhang. Freshness constraints of an age of information based event-triggered Kalman consensus filter algorithm over a wireless sensor network[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(1): 51-67.

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%A Yahui Li
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%A Youmin Zhang
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T1 - Freshness constraints of an age of information based event-triggered Kalman consensus filter algorithm over a wireless sensor network
A1 - Rui Wang
A1 - Yahui Li
A1 - Hui Sun
A1 - Youmin Zhang
J0 - Frontiers of Information Technology & Electronic Engineering
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2000206

This paper presents the design of a new event-triggered Kalman consensus filter (ET-KCF) algorithm for use over a wireless sensor network (WSN). This algorithm is based on information freshness, which is calculated as the age of information (AoI) of the sampled data. The proposed algorithm integrates the traditional event-triggered mechanism, information freshness calculation method, and Kalman consensus filter (KCF) algorithm to estimate the concentrations of pollutants in the aircraft more efficiently. The proposed method also considers the influence of data packet loss and the aircraft’s loss of communication path over the WSN, and presents an AoI-freshness-based threshold selection method for the ET-KCF algorithm, which compares the packet AoI to the minimum average AoI of the system. This method can obviously reduce the energy consumption because the transmission of expired information is reduced. Finally, the convergence of the algorithm is proved using the Lyapunov stability theory and matrix theory. Simulation results show that this algorithm has better fault tolerance compared to the existing KCF and lower power consumption than other ET-KCFs.





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