Volume 15, Issue 1 (Special Issue on AI in ICT 2023)                   2023, 15(1): 1-15 | Back to browse issues page

XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Nopahari S, Gharaee H, Khademzadeh A. Selfish Node Detection Based on GA and Learning Automata in IoT. International Journal of Information and Communication Technology Research 2023; 15 (1) : 1
URL: http://ijict.itrc.ac.ir/article-1-535-en.html
1- Computer engineering department, Science and Research Branch, Islamic Azad University Tehran, Iran
2- Iran Telecommunication Research Center (ITRC) Tehran, Iran , gharaee@itrc.ac.ir
3- Iran Telecommunication Research Center (ITRC) Tehran, Iran
Abstract:   (732 Views)
It is critical to increasing the network throughput on the internet of things with short-range nodes. Nodes prevent to cooperate with other nodes are known as selfish nodes. The proposed method for discovering the selfish node is based on genetic algorithm and learning automata. It consists of three phases of setup and clustering, the best routing selection based on genetic algorithm, and finally, the learning and update phase. The clustering algorithm implemented in the first phase. In the second phase, the neighbor node selected for forwarding the packet in which has a high value of fitness function. In the third phase, each node monitors its neighbor nodes and uses the learning automata system to identify the selfish nodes. The results of the simulation has shown the detection accuracy of selfish nodes in comparison with the existing methods average 10 %, and the false positive rate has decreased by 5 %.
Article number: 1
Full-Text [PDF 963 kb]   (294 Downloads)    
Type of Study: Research | Subject: Network

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.