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Erschienen in: Wireless Networks 6/2019

02.02.2019

An improved adaptive dual prediction scheme for reducing data transmission in wireless sensor networks

verfasst von: Hidaya Liazid, Mohamed Lehsaini, Abdelkrim Liazid

Erschienen in: Wireless Networks | Ausgabe 6/2019

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Abstract

Currently one of the main problem for wireless networks is the medium access control. Hence, the number of data transmissions in wireless sensor networks should be optimized to support more applications and a higher diversity of sensed parameters. In addition, minimizing energy consumption of sensor nodes constitutes one of the main ways to prolong network lifetime. One way to achieve this objective is the exploitation of data prediction technique. This paper presents an innovative idea improving the adaptive dual prediction algorithm without recourse to the data history table to update the model parameters when it drifts. The idea is to exploit immediately the new model parameters performed from the stored ones corresponding to the models used previously during the past prediction phases and eliminated when the threshold imposed by the user exceeded. We carried out simulations using real data of meteorological parameters. We show that our approach achieves up to 99% communication reduction with no significant loss in accuracy.

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Metadaten
Titel
An improved adaptive dual prediction scheme for reducing data transmission in wireless sensor networks
verfasst von
Hidaya Liazid
Mohamed Lehsaini
Abdelkrim Liazid
Publikationsdatum
02.02.2019
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 6/2019
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-019-01950-7

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