A Distributed Routing-Aware Deployment Algorithm for Underwater Sensor Networks

Deployment is the primary step of topology management, and designing efficient deployment schemes can optimize the network coverage performance and benefit the network data collection. This article proposes a distributed routing-aware self-adjusting deployment algorithm for underwater sensor network...

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Veröffentlicht in:IEEE sensors journal 2024-06, Vol.24 (12), p.20040-20053
Hauptverfasser: Shen, Zhongwei, Yin, Hongxi
Format: Artikel
Sprache:eng
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Zusammenfassung:Deployment is the primary step of topology management, and designing efficient deployment schemes can optimize the network coverage performance and benefit the network data collection. This article proposes a distributed routing-aware self-adjusting deployment algorithm for underwater sensor networks (UWSNs) with unevenly distributed interested targets, which consists of two main processes, i.e., the initial deployment and the node redeployment. During the initial deployment phase, an energy-efficient method of node energy assignment is designed considering the characteristics of the opportunistic routing mechanisms for UWSNs and the change in the employed network routing protocols. In the redeployment phase, a node position adjustment method based on the virtual force (VF)-directed particle swarm optimization (PSO) algorithm is designed, where nodes can cooperate to cover more interested targets in a distributed and adaptive manner. Unlike the existing related works, this research especially considers the routing mechanisms and the practical system models of UWSNs when designing the deployment scheme. According to simulation experiments, compared with the relevant algorithms, when the proposed deployment algorithm is carried out along with the routing process, the network coverage ratio can be raised by approximately 5%, and various routing performances are all improved, in particular, the number of collected packets during the network lifetime is increased by approximately 30%.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2024.3396145