Please use this identifier to cite or link to this item:
https://hdl.handle.net/11499/56533| Title: | Maximizing Nano-Sensor Node Coverage using BWO in WNSNs | Authors: | Gulec, O. Sahin, E. |
Keywords: | Black Widow optimization Internet of Nano-Things Node Coverage Wireless Nano-Sensor Networks Biomimetics Clustering algorithms Nanosensors Sensor nodes Black widow optimization Energy constraint Internet of nano-thing Metaheuristic Nano-sensors Network operations Node coverage Optimisations Sensors network Wireless nano-sensor network Genetic algorithms |
Publisher: | Institute of Electrical and Electronics Engineers Inc. | Abstract: | Due to the energy constraints of nano-sensors, all network operations should be optimized in Wireless Nano-Sensor Networks (WNSNs). Nature-inspired metaheuristics have been widely used for solving the network problems such as routing, clustering, security and such areas in the literature. Therefore, in this paper, Black Widow optimization (BWO) based nano-node clustering algorithm is proposed in order to achieve maximum node coverage on WNSNs. The proposed algorithm is compared with 2 different Genetic Algorithm (GA) setups. According to the results, the proposed method successfully covers the nano-nodes by the chosen head nodes on the network up to 99.876% on average. © 2023 IEEE. | Description: | 10th International Conference on Wireless Networks and Mobile Communications, WINCOM 2023 -- 26 October 2023 through 28 October 2023 -- 194643 | URI: | https://doi.org/10.1109/WINCOM59760.2023.10323003 https://hdl.handle.net/11499/56533 |
ISBN: | 9798350329674 |
| Appears in Collections: | İktisadi ve İdari Bilimler Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
Show full item record
CORE Recommender
SCOPUSTM
Citations
1
checked on Oct 13, 2024
Page view(s)
44
checked on Aug 24, 2024
Google ScholarTM
Check
Altmetric
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.