Energy Prediction Model Based on Kernel Partial Least Squares for Energy Harvesting Wireless Sensor Network

2017 ◽  
pp. 138-145
Author(s):  
Xuecai Bao
Keyword(s):  
Wireless Sensor Network ◽  
Energy Harvesting ◽  
Prediction Model ◽  
Least Squares ◽  
Sensor Network ◽  
Partial Least Squares ◽  
Wireless Sensor ◽  
Energy Prediction ◽  
Kernel Partial Least Squares ◽  
Model Based

scholarly journals Adaptive LINE-P: An Adaptive Linear Energy Prediction Model for Wireless Sensor Network Nodes

Sensors ◽  
2018 ◽  
Vol 18 (4) ◽  
pp. 1105 ◽  
Author(s):  
Faisal Ahmed ◽  
Gert Tamberg ◽  
Yannick Le Moullec ◽  
Paul Annus
Keyword(s):  
Wireless Sensor Network ◽  
Prediction Model ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Network Nodes ◽  
Energy Prediction ◽  
Line P

Multi-Source Hybrid Energy Harvesting Wireless Sensor Network Framework for Addressing Energy Unpredictability Issues

2021 ◽  
Vol 57 ◽  
pp. 225-241
Author(s):  
Aditi Paul ◽  
Indu Pandey
Keyword(s):  
Wireless Sensor Network ◽  
Energy Harvesting ◽  
Sensor Network ◽  
Complex Structure ◽  
Research Direction ◽  
Ease Of Use ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Functional Efficiency ◽  
Design Paradigm

Energy harvesting wireless sensor network (EH-WSN) harvests energy from the environment to supply power to the sensor nodes which apparently enhances their lifetime. However, the unpredictable nature of the resources throws challenges to the sustainability of energy supply for the continuous network operation. This creates a gap between unstable energy harvesting rates & energy requirements of the nodes of the network. The state-of-the-art algorithms proposed so far to address this problem domain are not able to bridge the gap fully to standardize the framework. Hence there is considerable scope of research to create a trade-off between EH techniques and specially designed protocols for in EH-WSN. Current study evaluates the performance and efficiency of some futuristic techniques which incorporate advanced tools and algorithms. The study aims to identify the strength and weaknesses of the proposed techniques which can emerge specific research requirement in this field. Finally, we propose a research direction towards Multi-source Hybrid EH-WSN (MHEHWSN) which is able to maximize energy availability and functional efficiency. The scope of this study is to develop a notion of a framework which eliminates the limitations of very recent techniques of EH-WSN by including multiple energy resources to extract required energy even in presence of unpredictability. However, keeping in mind the ease of use and less complex structure Multi-source hybrid EH technique requires a careful design paradigm.

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