In-network data processing approach for heterogeneous wireless sensor networks

A wireless sensor network (WSN) is a set of special-ized devices that commonly monitor environmental and physical conditions. A critical aspect of applications with WSNs is their limited resources especially in multivariate sensor features when transmitting large amount of data from the nodes to the...

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Bibliographic Details
Published in2022 International Wireless Communications and Mobile Computing (IWCMC) pp. 536 - 541
Main Authors Atoui, Ibrahim, Makhoul, Abdallah, Couturier, Raphael, Laiymani, David
Format Conference Proceeding
LanguageEnglish
Published IEEE 30.05.2022
Subjects
Base stations
data aggregation
Data integrity
data reduction
Fitting
Heterogeneous WSN
Power demand
similarity functions
Simulation
Wireless communication
Wireless sensor networks
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Summary:A wireless sensor network (WSN) is a set of special-ized devices that commonly monitor environmental and physical conditions. A critical aspect of applications with WSNs is their limited resources especially in multivariate sensor features when transmitting large amount of data from the nodes to the base station. The aim is then to optimize power consumption during data transmission by using data reduction methods. In this article, we study multivariate data reduction at node's level. We propose a new efficient model based on reducing collected data by aggregation and polynomial regression. We evaluate and compare our method with existing data aggregation techniques, and with the following well-known compression techniques (xz, bzip2, brotli and gzip). The simulation results show that our approach outperforms the existing methods and offers a good approximation of data quality with small approximation errors.
ISSN:2376-6506
DOI:10.1109/IWCMC55113.2022.9824990