Loading [a11y]/accessibility-menu.js
Spatio-Temporal Compressive Sensing-Based Data Gathering in Wireless Sensor Networks | IEEE Journals & Magazine | IEEE Xplore

Spatio-Temporal Compressive Sensing-Based Data Gathering in Wireless Sensor Networks


Abstract:

Sensory data in many wireless sensor networks feature spatio-temporal correlations, and compressive sensing (CS) plays an important role in energy-efficient data gatherin...Show More

Abstract:

Sensory data in many wireless sensor networks feature spatio-temporal correlations, and compressive sensing (CS) plays an important role in energy-efficient data gathering. In this letter, we design a new CS-based data gathering algorithm, utilizing random sampling and random walks to select sensory data in temporal and spatial domains, respectively. Each measurement is obtained by summing the selected data. A novel sensing matrix is also designed based on the adjacency matrix of an unbalanced expander graph. Simulation shows that our proposed algorithm reduces energy consumption by up to 50.0% compared to the existing algorithms in a daily sea surface temperature measurement scenario.
Published in: IEEE Wireless Communications Letters ( Volume: 7, Issue: 2, April 2018)
Page(s): 198 - 201
Date of Publication: 20 October 2017

ISSN Information:

Funding Agency:


References

References is not available for this document.