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A probabilistic and highly efficient topology control algorithm for underwater cooperating AUV networks
Universidad Politecnica de Madrid, Madrid, Spain .
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-5224-8302
Instituto de Telecomunicacoes, Lisboa, Portugal .
Universidade de Aveiro, Aveiro, Portugal .
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2017 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 17, no 5, 1022Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
MDPI AG , 2017. Vol. 17, no 5, 1022
Keyword [en]
AUV, Probabilistic, Topology control, Transmission power adjustment, Underwater network, Fuzzy logic, MESH networking, Scattering parameters, Topology, Unmanned surface vehicles, Vehicles, Wireless sensor networks, Autonomous underwater vehicles (AUVs), Reliable communication, Topology control algorithms, Transmission power, Underwater environments, Underwater networks, Autonomous underwater vehicles
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:mdh:diva-35525DOI: 10.3390/s17051022Scopus ID: 2-s2.0-85019062118OAI: oai:DiVA.org:mdh-35525DiVA: diva2:1104448
Available from: 2017-06-01 Created: 2017-06-01 Last updated: 2017-06-01Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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