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Wireless Personal Communications
Erschienen in: Wireless Personal Communications 2/2021

05.01.2021

Energy Efficient Data Gathering using Spatio-temporal Compressive Sensing for WSNs

verfasst von: K. Sekar, K. Suganya Devi, P. Srinivasan

Erschienen in: Wireless Personal Communications | Ausgabe 2/2021

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Abstract

In recent times, the wireless sensor network (WSN) has been designed to save energy for prolonging its lifetime. Minimize the implementation cost and energy utilization of sensors, and various data compression techniques have been used. We propose a new algorithm, semi-variance based compressive sensing (SCS), in this paper. The proposed scheme works with the spatio-temporal correlation of the signal and its performance investigated based on energy utilization and data quality. The new technique outperforms the existing data compression methods discussed in the literature survey. The simulation results prove that SCS effectively minimizes the computational and transmission cost of data and extends the life period of the WSN.
Vorheriger Artikel Enhancement of Efficiency and Performance Gain of Massive MIMO System Using Trial-Based Rider Optimization Algorithm
Nächster Artikel Prediction Based QoS Management in Replicated DRTDBS

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Metadaten
Titel
Energy Efficient Data Gathering using Spatio-temporal Compressive Sensing for WSNs
verfasst von
K. Sekar
K. Suganya Devi
P. Srinivasan
Publikationsdatum
05.01.2021
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 2/2021
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-020-07922-x

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