A probabilistic and highly efficient topology control algorithm for underwater cooperating AUV networks

Li, Ning and Cürüklü, Baran and Bastos, Joaquim and Sucasas, Victor and Sánchez Fernández, José Antonio and Rodríguez, Jonathan (2017). A probabilistic and highly efficient topology control algorithm for underwater cooperating AUV networks. "Sensors", v. 17 (n. 5); pp. 1-23. ISSN 1424-8220. https://doi.org/10.3390/s17051022.

Description

Title: A probabilistic and highly efficient topology control algorithm for underwater cooperating AUV networks
Author/s:
  • Li, Ning
  • Cürüklü, Baran
  • Bastos, Joaquim
  • Sucasas, Victor
  • Sánchez Fernández, José Antonio
  • Rodríguez, Jonathan
Item Type: Article
Título de Revista/Publicación: Sensors
Date: May 2017
Volume: 17
Subjects:
Freetext Keywords: topology control; underwater network; AUV; probabilistic; transmission power adjustment
Faculty: E.T.S.I. y Sistemas de Telecomunicación (UPM)
Department: Ingeniería Telemática y Electrónica
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (5MB) | Preview

Abstract

The aim of the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) project is to make autonomous underwater vehicles (AUVs), remote operated vehicles (ROVs) and unmanned surface vehicles (USVs) more accessible and useful. To achieve cooperation and communication between different AUVs, these must be able to exchange messages, so an efficient and reliable communication network is necessary for SWARMs. In order to provide an efficient and reliable communication network for mission execution, one of the important and necessary issues is the topology control of the network of AUVs that are cooperating underwater. However, due to the specific properties of an underwater AUV cooperation network, such as the high mobility of AUVs, large transmission delays, low bandwidth, etc., the traditional topology control algorithms primarily designed for terrestrial wireless sensor networks cannot be used directly in the underwater environment. Moreover, these algorithms, in which the nodes adjust their transmission power once the current transmission power does not equal an optimal one, are costly in an underwater cooperating AUV network. Considering these facts, in this paper, we propose a Probabilistic Topology Control (PTC) algorithm for an underwater cooperating AUV network. In PTC, when the transmission power of an AUV is not equal to the optimal transmission power, then whether the transmission power needs to be adjusted or not will be determined based on the AUV’s parameters. Each AUV determines their own transmission power adjustment probability based on the parameter deviations. The larger the deviation, the higher the transmission power adjustment probability is, and vice versa. For evaluating the performance of PTC, we combine the PTC algorithm with the Fuzzy logic Topology Control (FTC) algorithm and compare the performance of these two algorithms. The simulation results have demonstrated that the PTC is efficient at reducing the transmission power adjustment ratio while improving the network performance.

Funding Projects

TypeCodeAcronymLeaderTitle
Horizon 2020662107SWARMUNIVERSIDAD POLITÉCNICA DE MADRIDSmart and Networking Underwater Robots in Cooperation Meshes
Government of SpainPCIN-2014-022-C02-02UnspecifiedUnspecifiedUnspecified

More information

Item ID: 51566
DC Identifier: http://oa.upm.es/51566/
OAI Identifier: oai:oa.upm.es:51566
DOI: 10.3390/s17051022
Official URL: http://www.mdpi.com/1424-8220/17/5/1022/htm
Deposited by: Memoria Investigacion
Deposited on: 17 Jan 2019 16:45
Last Modified: 30 Apr 2019 10:02
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM