Correlated Spatio-Temporal Data Collection in Wireless Sensor Networks Based on Low Rank Matrix Approximation and Optimized Node Sampling

Correlated Spatio-Temporal Data Collection in Wireless Sensor Networks Based on Low Rank Matrix Approximation and Optimized Node Sampling

The emerging low rank matrix approximation (LRMA) method provides an energy efficient scheme for data collection in wireless sensor networks (WSNs) by randomly sampling a subset of sensor nodes for data sensing. However, the existing LRMA based methods generally underutilize the spatial or temporal...

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Bibliographic Details
Main Authors: Xinglin Piao, Yongli Hu, Yanfeng Sun, Baocai Yin, Junbin Gao
Format: Article
Language:English
Published: MDPI AG 2014-12-01
Series:Sensors
Subjects:
wireless sensor networks
data collection
low rank matrix approximation.
Online Access:http://www.mdpi.com/1424-8220/14/12/23137

Internet

http://www.mdpi.com/1424-8220/14/12/23137

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