Game-theory-based clustering scheme for energy balancing in underwater acoustic sensor networks
The underwater acoustic sensor network (UASN) is a specific deployment of Internet-of-Things (IoT) technology in the underwater environment, since energy constraints limit the lifetime of UASNs, effectively balancing the energy consumption of acoustic sensor nodes in UASNs is important to maximize t...
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sg-ntu-dr.10356-1598472022-07-04T07:44:18Z Game-theory-based clustering scheme for energy balancing in underwater acoustic sensor networks Xing, Guanglin Chen, Yumeng Hou, Rui Dong, Mianxiong Zeng, Deze Luo, Jiangtao Ma, Maode School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Energy Consumption Routing The underwater acoustic sensor network (UASN) is a specific deployment of Internet-of-Things (IoT) technology in the underwater environment, since energy constraints limit the lifetime of UASNs, effectively balancing the energy consumption of acoustic sensor nodes in UASNs is important to maximize the amount of information collected and to prolong the network lifetime. Node clustering is widely regarded as one of the most important energy-efficient schemes for UASNs. However, most existing clustering schemes focus on the cooperation-based election of cluster headers (CHs) in a centralized manner. Due to the limited energy capacity, acoustic sensor nodes are designed to save their own energy, hindering the realization of such cooperation. To address this issue in this article, game theory is applied to UASNs to balance network energy consumption and model acoustic sensor nodes as rational and selfish players. Specifically, a game-theory-based clustering (GTC) scheme for UASNs is developed. In the CH election phase, each node makes a decision in pursuit of a greater payoff based on the Nash equilibrium. An incentive mechanism is invented to induce nodes to make more beneficial collective decisions and plays a role in the CH rotation to effectively balance the energy consumption. Meanwhile, the network area is divided into nonuniform sectors to ensure the energy consumption of the CH is more evenly distributed. Simulation results show that the proposed GTC scheme can effectively balance network energy consumption and extend the network lifetime. This work was supported in part by the National Natural Science Foundation of China under Grant 61972424; in part by JSPS KAKENHI under Grant JP20F20080; and in part by the Special Fund for Basic Scientific Research of Central College, SCUEC, under Grant CZT20025. 2022-07-04T07:44:18Z 2022-07-04T07:44:18Z 2021 Journal Article Xing, G., Chen, Y., Hou, R., Dong, M., Zeng, D., Luo, J. & Ma, M. (2021). Game-theory-based clustering scheme for energy balancing in underwater acoustic sensor networks. IEEE Internet of Things Journal, 8(11), 9005-9013. https://dx.doi.org/10.1109/JIOT.2021.3055857 2327-4662 https://hdl.handle.net/10356/159847 10.1109/JIOT.2021.3055857 2-s2.0-85100733313 11 8 9005 9013 en IEEE Internet of Things Journal © 2021 IEEE. All rights reserved. |
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Engineering::Electrical and electronic engineering Energy Consumption Routing Xing, Guanglin Chen, Yumeng Hou, Rui Dong, Mianxiong Zeng, Deze Luo, Jiangtao Ma, Maode Game-theory-based clustering scheme for energy balancing in underwater acoustic sensor networks |
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The underwater acoustic sensor network (UASN) is a specific deployment of Internet-of-Things (IoT) technology in the underwater environment, since energy constraints limit the lifetime of UASNs, effectively balancing the energy consumption of acoustic sensor nodes in UASNs is important to maximize the amount of information collected and to prolong the network lifetime. Node clustering is widely regarded as one of the most important energy-efficient schemes for UASNs. However, most existing clustering schemes focus on the cooperation-based election of cluster headers (CHs) in a centralized manner. Due to the limited energy capacity, acoustic sensor nodes are designed to save their own energy, hindering the realization of such cooperation. To address this issue in this article, game theory is applied to UASNs to balance network energy consumption and model acoustic sensor nodes as rational and selfish players. Specifically, a game-theory-based clustering (GTC) scheme for UASNs is developed. In the CH election phase, each node makes a decision in pursuit of a greater payoff based on the Nash equilibrium. An incentive mechanism is invented to induce nodes to make more beneficial collective decisions and plays a role in the CH rotation to effectively balance the energy consumption. Meanwhile, the network area is divided into nonuniform sectors to ensure the energy consumption of the CH is more evenly distributed. Simulation results show that the proposed GTC scheme can effectively balance network energy consumption and extend the network lifetime. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Xing, Guanglin Chen, Yumeng Hou, Rui Dong, Mianxiong Zeng, Deze Luo, Jiangtao Ma, Maode |
format |
Article |
author |
Xing, Guanglin Chen, Yumeng Hou, Rui Dong, Mianxiong Zeng, Deze Luo, Jiangtao Ma, Maode |
author_sort |
Xing, Guanglin |
title |
Game-theory-based clustering scheme for energy balancing in underwater acoustic sensor networks |
title_short |
Game-theory-based clustering scheme for energy balancing in underwater acoustic sensor networks |
title_full |
Game-theory-based clustering scheme for energy balancing in underwater acoustic sensor networks |
title_fullStr |
Game-theory-based clustering scheme for energy balancing in underwater acoustic sensor networks |
title_full_unstemmed |
Game-theory-based clustering scheme for energy balancing in underwater acoustic sensor networks |
title_sort |
game-theory-based clustering scheme for energy balancing in underwater acoustic sensor networks |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/159847 |
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1738844907218403328 |