Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/56062
Title: Obstacle Aware Density Based Nano-Router Localization in IoNT
Authors: Sahin, E.
Gulec, O.
Keywords: Internet of Nuno-Things
Machine Learning
Nano-Router Localization
Obstacle
Wireless Nano-Sensor Networks
Nanosensors
Wireless sensor networks
Dense network
Density-based
Internet of nuno-thing
Localisation
Machine-learning
Nano-router localization
Nano-sensors
Obstacle
Sensors network
Wireless nano-sensor network
Machine learning
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: Wireless Nano-Sensor Networks (WNSNs) are dense networks consisting of many nano-machines that work on nano-scale mediums in Internet of Nano-Things (IoNT) applications. In these kinds of mediums, the communication range is limited and could be interrupted by obstacles. Thus, the nano-router should be positioned in the correct location in order to achieve high data flow accuracy. Therefore, in this paper, a Machine Learning-supported obstacle-aware density-based nano-router localization algorithm is proposed in IoNT applications. The proposed algorithm is compared with the networks having only a nano-router which is placed at [0, 0] coordinates of the network. According to the results, the proposed algorithm successfully finds the best locations of the nano-routers on the network due to the nano-node density caused by the obstacles on the medium. © 2023 IEEE.
Description: 8th International Conference on Computer Science and Engineering, UBMK 2023 -- 13 September 2023 through 15 September 2023 -- 193873
URI: http://dx.doi.org/10.1109/UBMK59864.2023.10286772
https://hdl.handle.net/11499/56062
ISBN: 9798350340815
Appears in Collections:İktisadi ve İdari Bilimler Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Show full item record



CORE Recommender

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.