Red Deer Algorithm based nano-sensor node clustering for IoNT. (April 2023)

• Record Type: Journal Article
• Authors: Gulec, Omer; Sahin, Emre
• Is Part Of: Journal of network and computer applications. Volume 213(2023)
• Publication Date: 2023-04
• Subjects: Internet of Nano-Things -- Wireless nano-sensor networks -- Red Deer Algorithm -- Clustering -- Coverage -- Metaheuristics; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2023.103591
• Languages: English
• ISSNs: 1084-8045

Abstract

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 nano RDA, 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. nano RDA is compared with two different Genetic Algorithm (GA) setups. According to the results, nano RDA 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.