Dynamic mobile anchor path planning for underwater wireless sensor networks

In an underwater wireless sensor network (UWSN), the location of the sensor nodes plays a significant role in the localization process. The location information is obtained by using the known positions of anchor nodes. For underwater environments, instead of using various static anchor nodes, mobile...

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Bibliographic Details
Main Authors: Mohamed, Mohammad Hafiz, Abu Bakar, Kamalrulnizam, Isnin, Ismail Fauzi, M. Zaki, M. Zulkifli, Herman, Herman, Zuhra, Fatima Tul
Format: Article
Language:English
Published: Universitas Ahmad Dahlan 2021
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Online Access:http://eprints.utm.my/id/eprint/94101/1/IsmailFauziIsnin2021_DynamicMobileAnchorPathPlanning.pdf
http://eprints.utm.my/id/eprint/94101/
http://dx.doi.org/10.12928/TELKOMNIKA.v19i4.19016
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Summary:In an underwater wireless sensor network (UWSN), the location of the sensor nodes plays a significant role in the localization process. The location information is obtained by using the known positions of anchor nodes. For underwater environments, instead of using various static anchor nodes, mobile anchor nodes are more efficient and cost-effective to cover the monitoring area. Nevertheless, the utilization of these mobile anchors requires adequate path planning strategy. Mzost of the path planning algorithms do not consider irregular deployment, caused by the effects of water currents. Consequently, this leads towards the inefficient energy consumption by mobile anchors due to unnecessary transmission of beacon messages at unnecessary areas. Therefore, an efficient dynamic mobile path planning (EDMPP) algorithm to tackle the irregular deployment and non-collinear virtual beacon point placement, targeting the underwater environment settings is presented in this paper. In addition, EDMPP controls the redundant beacon message deployment and overlapping, for beacon message distribution in mobile assistant localization. The simulation results show that the performance of the EDMPP is improved by increasing the localization accuracy and decreasing the energy consumption with optimum path length.