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

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