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https://hdl.handle.net/11499/51065
Title: | Red Deer Algorithm based nano-sensor node clustering for IoNT | Authors: | Güleç, Ömer Şahin, Emre |
Keywords: | Internet of Nano-Things Wireless nano-sensor networks Red Deer Algorithm Clustering Coverage Metaheuristics |
Publisher: | Academic Press Ltd- Elsevier Science Ltd | Abstract: | Node connectivity is a crucial issue for collecting and transmitting the values of the medium at nano-scale in Wireless Nano-Sensor Networks (WNSNs). This provides the network to be online when the sensor nodes maintain connectivity among themselves. Therefore, efficient connectivity methods need to be developed for permanent connection on the network. The basic way to provide connectivity over the network is clustering -based solutions which build efficient routing paths between the nodes. On the other hand, meta-heuristics are prominent methods to be preferred in order to select special nodes as cluster heads. In this paper, a modern meta-heuristic method, the Red Deer Algorithm (RDA) based distributed nano-sensor node clustering algorithm, namely nanoRDA, is proposed in order to provide efficient communication between nano-sensor nodes by selecting cluster heads on WNSNs in Internet of Nano-Things (IoNT) applications. nanoRDA is compared with two different Genetic Algorithm (GA) setups. According to the results, nanoRDA covers all non-cluster head nodes up to 99.38% on average all over the nano-scale networks while selecting fewer cluster heads than GA-based solutions. | URI: | https://doi.org/10.1016/j.jnca.2023.103591 https://hdl.handle.net/11499/51065 |
ISSN: | 1084-8045 1095-8592 |
Appears in Collections: | İktisadi ve İdari Bilimler Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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