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Open AccessArticle

Game Theoretic Solution for Power Management in IoT-Based Wireless Sensor Networks

1
Institute of Computing, Kohat University of Science and Technology, Kohat 26000, Pakistan
2
Department of Physics, Kohat University of Science and Technology, Kohat 26000, Pakistan
3
Department of Electronics Engineering, Hankuk University of Foreign Studies, Yongin 17035, Korea
4
Universitat Politecnica de Valencia, C/Paranimf, 1, Grao de Gandia, Gandia, 46370 Valencia, Spain
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(18), 3835; https://doi.org/10.3390/s19183835
Received: 2 August 2019 / Revised: 25 August 2019 / Accepted: 2 September 2019 / Published: 5 September 2019
(This article belongs to the Special Issue Recent Advances in Internet of Things and Sensor Networks)
Internet of things (IoT) is a very important research area, having many applications such as smart cities, intelligent transportation system, tracing, and smart homes. The underlying technology for IoT are wireless sensor networks (WSN). The selection of cluster head (CH) is significant as a part of the WSN’s optimization in the context of energy consumption. In WSNs, the nodes operate on a very limited energy source, therefore, the routing protocols designed must meet the optimal utilization of energy consumption in such networks. Evolutionary games can be designed to meet this aspect by providing an adequately efficient CH selection mechanism. In such types of mechanisms, the network nodes are considered intelligent and independent to select their own strategies. However, the existing mechanisms do not consider a combination of many possible parameters associated with the smart nodes in WSNs, such as remaining energy, selfishness, hop-level, density, and degree of connectivity. In our work, we designed an evolutionary game-based approach for CH selection, combined with some vital parameters associated with sensor nodes and the entire networks. The nodes are assumed to be smart, therefore, the aspect of being selfish is also addressed in this work. The simulation results indicate that our work performs much better than typical evolutionary game-based approaches. View Full-Text
Keywords: evolutionary game; energy efficiency; game theory; wireless sensor networks evolutionary game; energy efficiency; game theory; wireless sensor networks
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MDPI and ACS Style

Sohail, M.; Khan, S.; Ahmad, R.; Singh, D.; Lloret, J. Game Theoretic Solution for Power Management in IoT-Based Wireless Sensor Networks. Sensors 2019, 19, 3835.

AMA Style

Sohail M, Khan S, Ahmad R, Singh D, Lloret J. Game Theoretic Solution for Power Management in IoT-Based Wireless Sensor Networks. Sensors. 2019; 19(18):3835.

Chicago/Turabian Style

Sohail, Muhammad; Khan, Shafiullah; Ahmad, Rashid; Singh, Dhananjay; Lloret, Jaime. 2019. "Game Theoretic Solution for Power Management in IoT-Based Wireless Sensor Networks" Sensors 19, no. 18: 3835.

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