Routing strategy of reducing energy consumption for underwater data collection

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....

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Bibliographic Details
Published inIntelligent and converged networks Vol. 2; no. 3; pp. 163 - 176
Main Authors Wu, Jiehong, Sun, Xichun, Wu, Jinsong, Han, Guangjie
Format Journal Article
LanguageEnglish
Published Tsinghua University Press 01.09.2021
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ISSN2708-6240
2708-6240
DOI10.23919/ICN.2021.0012

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Summary: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.
ISSN:2708-6240
2708-6240
DOI:10.23919/ICN.2021.0012