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Energy Efficiency of Ultra-Low-Power Bicycle Wireless Sensor Networks Based on a Combination of Power Reduction Techniques
Joint Authors
Nordin, Rosdiadee
Gharghan, Sadik Kamel
Ismail, Mahamod
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-21, 21 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-08-23
Country of Publication
Egypt
No. of Pages
21
Main Subjects
Abstract EN
In most wireless sensor network (WSN) applications, the sensor nodes (SNs) are battery powered and the amount of energy consumed by the nodes in the network determines the network lifespan.
For future Internet of Things (IoT) applications, reducing energy consumption of SNs has become mandatory.
In this paper, an ultra-low-power nRF24L01 wireless protocol is considered for a bicycle WSN.
The power consumption of the mobile node on the cycle track was modified by combining adjustable data rate, sleep/wake, and transmission power control (TPC) based on two algorithms.
The first algorithm was a TPC-based distance estimation, which adopted a novel hybrid particle swarm optimization-artificial neural network (PSO-ANN) using the received signal strength indicator (RSSI), while the second algorithm was a novel TPC-based accelerometer using inclination angle of the bicycle on the cycle track.
Based on the second algorithm, the power consumption of the mobile and master nodes can be improved compared with the first algorithm and constant transmitted power level.
In addition, an analytical model is derived to correlate the power consumption and data rate of the mobile node.
The results indicate that the power savings based on the two algorithms outperformed the conventional operation (i.e., without power reduction algorithm) by 78%.
American Psychological Association (APA)
Gharghan, Sadik Kamel& Nordin, Rosdiadee& Ismail, Mahamod. 2016. Energy Efficiency of Ultra-Low-Power Bicycle Wireless Sensor Networks Based on a Combination of Power Reduction Techniques. Journal of Sensors،Vol. 2016, no. 2016, pp.1-21.
https://search.emarefa.net/detail/BIM-1110595
Modern Language Association (MLA)
Gharghan, Sadik Kamel…[et al.]. Energy Efficiency of Ultra-Low-Power Bicycle Wireless Sensor Networks Based on a Combination of Power Reduction Techniques. Journal of Sensors No. 2016 (2016), pp.1-21.
https://search.emarefa.net/detail/BIM-1110595
American Medical Association (AMA)
Gharghan, Sadik Kamel& Nordin, Rosdiadee& Ismail, Mahamod. Energy Efficiency of Ultra-Low-Power Bicycle Wireless Sensor Networks Based on a Combination of Power Reduction Techniques. Journal of Sensors. 2016. Vol. 2016, no. 2016, pp.1-21.
https://search.emarefa.net/detail/BIM-1110595
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1110595