Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/56856
Title: An Effective Cluster Head Selection Algorithm using Machine Learning in IoNT
Authors: Gulec, O.
Keywords: Cluster Head Selection
Internet of Nano-Things
Machine Learning
Wireless Nano-Sensor Networks
Clustering algorithms
Internet of things
Learning algorithms
Nanosensors
Packet networks
Sensor nodes
Cluster-head selections
Cluster-heads
Clusterings
Efficient routing
Internet of nano-thing
Machine-learning
Nano-sensors
Selection algorithm
Sensors network
Wireless nano-sensor network
Machine learning
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: Clustering is the first technique that comes to mind in order to achieve efficient routing in sensor networks. Instead of transmitting the packets to each other, selecting a cluster head (CH) among the nodes is the best way to collect the packets from the cluster members which leads to saving energy, reducing network traffic, preventing packet loss and prolonging network lifetime. Cluster head selection (CHS) is a challenging process in a network therefore, CHS should be efficient and effective in Wireless Nano-Sensor Networks (WNSNs) due to the nano-domain characteristics. In this paper, an effective CHS algorithm using Machine Learning (ML) is proposed for Wireless Nano-Sensor Networks (WNSNs) and Internet of Nano-Things (IoNT) applications. The proposed algorithm (PA) is compared with an ordinary cluster head selection (OCHS) algorithm. According to the simulation results, PA provides nano-sensor node coverage on the network by 89.235% while it covers 20.355% more nano-nodes and spends 1.29 minutes less compared to OCHS on average. © 2023 IEEE.
Description: 12th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2023 -- 23 November 2023 through 25 November 2023 - 197147
URI: https://doi.org/10.1109/COMNETSAT59769.2023.10420624
https://hdl.handle.net/11499/56856
ISBN: 9798350341102
Appears in Collections:İktisadi ve İdari Bilimler Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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