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Intelligent and Converged Networks 2021, 2(3): 163-176 https://doi.org/10.23919/ICN.2021.0012
Open Access | Issue | Published: 01 September 2021

Routing strategy of reducing energy consumption for underwater data collection

Show Author's Information Jiehong Wu1( ),  Xichun Sun1,  Jinsong Wu2,  Guangjie Han3
School of Computer Science, Shenyang Aerospace University, Shenyang 110000, China
School of Artificial Intelligence, Guilin University of Electronic Technology, Guilin 541004, China, and also with the Department of Electrical Engineering, University of Chile, Santiago 518000, Chile
Department of Internet of Things Engineering, Hohai University, Changzhou 213022, China, and also with the State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
Keywords:
energy efficiency, underwater sensor network, balanced energy consumption, clustering scheme
Cite this article:
Wu J, Sun X, Wu J, et al. Routing strategy of reducing energy consumption for underwater data collection. Intelligent and Converged Networks, 2021, 2(3): 163-176. https://doi.org/10.23919/ICN.2021.0012
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Abstract Full text About this article

Underwater Wireless Sensor Networks (UWSNs) are widely used in many fields, such as regular marine monitoring and disaster warning. However, UWSNs are still subject to various limitations and challenges: ocean interferences and noises are high, bandwidths are narrow, and propagation delays are high. Sensor batteries have limited energy and are difficult to be replaced or recharged. Accordingly, the design of routing protocols is one of the solutions to these problems. Aiming at reducing and balancing network energy consumption and effectively extending the life cycle of UWSNs, this paper proposes a Hierarchical Adaptive Energy-efficient Clustering Routing (HAECR) strategy. First, this strategy divides hierarchical regions based on the depth of the sensor node in a three-dimensional (3D) space. Second, sensor nodes form different competition radii based on their own relevant attributes and remaining energy. Nodes in the same layer compete freely to form clusters of different sizes. Finally, the transmission path between clusters is determined according to comprehensive factors, such as link quality, and then the optimal route is planned. The simulation experiment is conducted in the monitoring range of the 3D space. The simulation results prove that the HAECR clustering strategy is superior to LEACH and UCUBB in terms of balancing and reducing energy consumption, extending the network lifetime, and increasing the number of data transmissions.


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About this article

Routing strategy of reducing energy consumption for underwater data collection

Show Author's information Jiehong Wu1( ), Xichun Sun1, Jinsong Wu2, Guangjie Han3
School of Computer Science, Shenyang Aerospace University, Shenyang 110000, China
School of Artificial Intelligence, Guilin University of Electronic Technology, Guilin 541004, China, and also with the Department of Electrical Engineering, University of Chile, Santiago 518000, Chile
Department of Internet of Things Engineering, Hohai University, Changzhou 213022, China, and also with the State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China

Abstract

Underwater Wireless Sensor Networks (UWSNs) are widely used in many fields, such as regular marine monitoring and disaster warning. However, UWSNs are still subject to various limitations and challenges: ocean interferences and noises are high, bandwidths are narrow, and propagation delays are high. Sensor batteries have limited energy and are difficult to be replaced or recharged. Accordingly, the design of routing protocols is one of the solutions to these problems. Aiming at reducing and balancing network energy consumption and effectively extending the life cycle of UWSNs, this paper proposes a Hierarchical Adaptive Energy-efficient Clustering Routing (HAECR) strategy. First, this strategy divides hierarchical regions based on the depth of the sensor node in a three-dimensional (3D) space. Second, sensor nodes form different competition radii based on their own relevant attributes and remaining energy. Nodes in the same layer compete freely to form clusters of different sizes. Finally, the transmission path between clusters is determined according to comprehensive factors, such as link quality, and then the optimal route is planned. The simulation experiment is conducted in the monitoring range of the 3D space. The simulation results prove that the HAECR clustering strategy is superior to LEACH and UCUBB in terms of balancing and reducing energy consumption, extending the network lifetime, and increasing the number of data transmissions.

Keywords: energy efficiency, underwater sensor network, balanced energy consumption, clustering scheme

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Received: 07 April 2021
Revised: 12 May 2021
Accepted: 16 May 2021
Published: 01 September 2021
Issue date: September 2021

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