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A Dynamic Surface Gateway Placement Scheme for Mobile Underwater Networks.
Liu, Jun; Guan, Wenxue; Han, Guangjie; Cui, Jun-Hong; Fiondella, Lance; Al-Bzoor, Manal.
Afiliación
  • Liu J; College of Computer Science and Technology, Jilin University, Changchun 130012, China. liujun1509@jlu.edu.cn.
  • Guan W; State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China. liujun1509@jlu.edu.cn.
  • Han G; College of Computer Science and Technology, Jilin University, Changchun 130012, China. guanwx18@mails.jlu.edu.cn.
  • Cui JH; College of Engineering, Nanjing Agricultural University, Nanjing 210095, China. hanguangjie@ieee.org.
  • Fiondella L; College of Internet of Things Engineering, Hohai University, 200 North Jinling Road, Changzhou 213022, China. hanguangjie@ieee.org.
  • Al-Bzoor M; State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China. hanguangjie@ieee.org.
Sensors (Basel) ; 19(9)2019 Apr 28.
Article en En | MEDLINE | ID: mdl-31035413
ABSTRACT
Deployment of surface-level gateways holds potential as an effective method to alleviate high-propagation delays and high-error probability in an underwater wireless sensor network (UWSN). This promise comes from reducing distances to underwater nodes and using radio waves to forward information to a control station. In an UWSN, a dynamic energy efficient surface-level gateway deployment is required to cope with the mobility of underwater nodes while considering the remote and three-dimensional nature of marine space. In general, deployment problems are usually modeled as an optimization problem to satisfy multiple constraints given a set of parameters. One previously published static deployment optimization framework makes assumptions about network workload, routing, medium access control performance, and node mobility. However, in real underwater environments, all these parameters are dynamic. Therefore, the accuracy of performance estimates calculated through static UWSN deployment optimization framework tends to be limited by nature. This paper presents the Prediction-Assisted Dynamic Surface Gateway Placement (PADP) algorithm to maximize the coverage and minimize the average end-to-end delay of a mobile underwater sensor network over a specified period. PADP implements the Interacting Multiple Model (IMM) tracking scheme to predict the positions of sensor nodes. The deployment is determined based on both current and predicted positions of sensor nodes, which enables better coverage and shorter end-to-end delay. PADP uses a branch-and-cut approach to solve the optimization problem efficiently, and employs a disjoint-set data structure to ensure connectivity. Simulation results illustrate that PADP significantly outperforms a static gateway deployment scheme.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2019 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2019 Tipo del documento: Article País de afiliación: China