Energy efficient data gathering in wireless sensor networks and internet of things with compressive sensing at sensor node

2016 ◽  
Author(s):  
Sonali Abhijeet Padalkar ◽  
Utkarsha Pacharaney
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Compressive Sensing ◽  
Energy Efficient ◽  
Sensor Node ◽  
Data Gathering ◽  
Wireless Sensor ◽  
Efficient Data

scholarly journals Coalition Formation Based Compressive Sensing in Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2331 ◽  
Author(s):  
Alireza Masoum ◽  
Nirvana Meratnia ◽  
Paul Havinga
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Compressive Sensing ◽  
Energy Efficient ◽  
Network Performance ◽  
Data Gathering ◽  
Data Accuracy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Efficient Data

Compressive sensing originates in the field of signal processing and has recently become a topic of energy-efficient data gathering in wireless sensor networks. In this paper, we propose an energy efficient distributed compressive sensing solution for sensor networks. The proposed solution utilizes sparsity distribution of signals to group sensor nodes into several coalitions and then implements localized compressive sensing inside coalitions. This solution improves data-gathering performance in terms of both data accuracy and energy consumption. The approach curbs both data-transmission costs and number of measurements. Coalition-based data gathering cuts transmission costs, and the number of measurements is reduced by scheduling sensor nodes and adjusting their sampling frequency. Our simulation showed that our approach enhances network performance by minimizing energy cost and improving data accuracy.

scholarly journals Novel Energy-Efficient Data Gathering Scheme Exploiting Spatial-Temporal Correlation for Wireless Sensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Ying Zhou ◽  
Lihua Yang ◽  
Longxiang Yang ◽  
Meng Ni
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Data Gathering ◽  
Temporal Correlation ◽  
Wireless Sensor ◽  
Selection Scheme ◽  
Efficient Data ◽  
Transmission Energy Consumption

A novel energy-efficient data gathering scheme that exploits spatial-temporal correlation is proposed for clustered wireless sensor networks in this paper. In the proposed method, dual prediction is used in the intracluster transmission to reduce the temporal redundancy, and hybrid compressed sensing is employed in the intercluster transmission to reduce the spatial redundancy. Moreover, an error threshold selection scheme is presented for the prediction model by optimizing the relationship between the energy consumption and the recovery accuracy, which makes the proposed method well suitable for different application environments. In addition, the transmission energy consumption is derived to verify the efficiency of the proposed method. Simulation results show that the proposed method has higher energy efficiency compared with the existing schemes, and the sink can recover measurements with reasonable accuracy by using the proposed method.

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