An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks
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School of Engineering Mastership, Pohang University of Science and Technology, 77 Cheongam-ro, Nam-gu, Pohang, Gyeongbuk 37673, Korea
2
Deptartment of Computer Engineering, Chosun University, 309 Pilmun-daero, Dong-gu, Gwangju 61452, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Sensors 2016, 16(7), 1009; https://doi.org/10.3390/s16071009
Received: 25 March 2016
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Revised: 17 June 2016
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Accepted: 25 June 2016
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Published: 30 June 2016
(This article belongs to the Section Sensor Networks)
A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD) scheme for CRSNs to prolong the network lifetime. Note that energy efficiency is the most important design consideration in CRSNs because it determines the network lifetime. The central part of the EGSD scheme consists of two spectrum selection algorithms: random selection and game-theory-based selection. The EGSD scheme also includes a clustering algorithm, spectrum characterization with a Markov chain, and cluster member coordination. Our performance study shows that EGSD outperforms the existing popular framework in terms of network lifetime and coordination overhead.
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Keywords:
cognitive radio; cognitive radio sensor network; energy-efficiency; game theory; spectrum decision
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MDPI and ACS Style
Salim, S.; Moh, S. An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks. Sensors 2016, 16, 1009. https://doi.org/10.3390/s16071009
AMA Style
Salim S, Moh S. An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks. Sensors. 2016; 16(7):1009. https://doi.org/10.3390/s16071009
Chicago/Turabian StyleSalim, Shelly, and Sangman Moh. 2016. "An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks" Sensors 16, no. 7: 1009. https://doi.org/10.3390/s16071009
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