scholarly journals A Distributed Compressive Sensing Technique for Data Gathering in Wireless Sensor Networks

2013 ◽  
Vol 21 ◽  
pp. 207-216 ◽  
Author(s):  
Alireza Masoum ◽  
Nirvana Meratnia ◽  
Paul J.M. Havinga
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Compressive Sensing ◽  
Data Gathering ◽  
Wireless Sensor ◽  
Distributed Compressive Sensing

scholarly journals Compressive Sensing-Based Clustering Joint Annular Routing Data Gathering Scheme for Wireless Sensor Networks

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 114639-114658 ◽  
Author(s):  
Yicong Yuan ◽  
Wei Liu ◽  
Tian Wang ◽  
Qingyong Deng ◽  
Anfeng Liu ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Compressive Sensing ◽  
Data Gathering ◽  
Wireless Sensor

Clustering and Compressive Data Gathering for Transmission Efficient Wireless Sensor Networks

2021 ◽  
pp. 28-55
Author(s):  
Utkarsha Sumedh Pacharaney ◽  
Ranjan Bala Jain ◽  
Rajiv Kumar Gupta
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Compressive Sensing ◽  
Data Gathering ◽  
Correlated Data ◽  
Wireless Sensor ◽  
Clustering Methods ◽  
Compression Technique ◽  
Spatially Correlated ◽  
Sensory Data

The chapter focuses on minimizing the amount of wireless transmission in sensory data gathering for correlated data field monitoring in wireless sensor networks (WSN), which is a major source of power consumption. Compressive sensing (CS) is a new in-node compression technique that is economically used for data gathering in an energy-constrained WSN. Among existing CS-based routing, cluster-based methods offer the most transmission-efficient architecture. Most CS-based clustering methods randomly choose nodes to form clusters, neglecting the topology structure. A novel base station (BS)-assisted cluster, spatially correlated cluster using compressive sensing (SCC_CS), is proposed to reduce number of transmissions in and form the cluster by exploiting spatial correlation based on geographical proximity. The proposed BS-assisted clustering scheme follows hexagonal deployment strategy. In SCC_CS, cluster heads are solely involved in data gathering and transmitting CS measurements to BS, saving intra-cluster communication cost, and thus, network life increases as proved by simulation.

scholarly journals 1-Bit Compressive Data Gathering for Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Jiping Xiong ◽  
Qinghua Tang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Compressive Sensing ◽  
State Of The Art ◽  
Data Gathering ◽  
Reconstruction Algorithm ◽  
Experimental Results ◽  
Wireless Sensor ◽  
Communication Overhead ◽  
Reconstruction Algorithms

Compressive sensing (CS) has been widely used in wireless sensor networks for the purpose of reducing the data gathering communication overhead in recent years. In this paper, we firstly apply 1-bit compressive sensing to wireless sensor networks to further reduce the communication overhead that each sensor needs to send. Furthermore, we propose a novel blind 1-bit CS reconstruction algorithm which outperforms other state-of-the-art blind 1-bit CS reconstruction algorithms under the settings of WSN. Experimental results on real sensor datasets demonstrate the efficiency of our method.

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