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SDN-IoT: SDN-based efficient clustering scheme for IoT using improved Sailfish optimization algorithm

The Internet of Things (IoT) includes billions of different devices and various applications that generate a huge amount of data. Due to inherent resource limitations, reliable and robust data transmission for a huge number of heterogenous devices is one of the most critical issues for IoT. Therefor...

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Autores principales: Mohammadi, Ramin, Akleylek, Sedat, Ghaffari, Ali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403188/
https://www.ncbi.nlm.nih.gov/pubmed/37547416
http://dx.doi.org/10.7717/peerj-cs.1424
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author Mohammadi, Ramin
Akleylek, Sedat
Ghaffari, Ali
author_facet Mohammadi, Ramin
Akleylek, Sedat
Ghaffari, Ali
author_sort Mohammadi, Ramin
collection PubMed
description The Internet of Things (IoT) includes billions of different devices and various applications that generate a huge amount of data. Due to inherent resource limitations, reliable and robust data transmission for a huge number of heterogenous devices is one of the most critical issues for IoT. Therefore, cluster-based data transmission is appropriate for IoT applications as it promotes network lifetime and scalability. On the other hand, Software Defined Network (SDN) architecture improves flexibility and makes the IoT respond appropriately to the heterogeneity. This article proposes an SDN-based efficient clustering scheme for IoT using the Improved Sailfish optimization (ISFO) algorithm. In the proposed model, clustering of IoT devices is performed using the ISFO model and the model is installed on the SDN controller to manage the Cluster Head (CH) nodes of IoT devices. The performance evaluation of the proposed model was performed based on two scenarios with 150 and 300 nodes. The results show that for 150 nodes ISFO model in comparison with LEACH, LEACH-E reduced energy consumption by about 21.42% and 17.28%. For 300 ISFO nodes compared to LEACH, LEACH-E reduced energy consumption by about 37.84% and 27.23%.
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spelling pubmed-104031882023-08-05 SDN-IoT: SDN-based efficient clustering scheme for IoT using improved Sailfish optimization algorithm Mohammadi, Ramin Akleylek, Sedat Ghaffari, Ali PeerJ Comput Sci Artificial Intelligence The Internet of Things (IoT) includes billions of different devices and various applications that generate a huge amount of data. Due to inherent resource limitations, reliable and robust data transmission for a huge number of heterogenous devices is one of the most critical issues for IoT. Therefore, cluster-based data transmission is appropriate for IoT applications as it promotes network lifetime and scalability. On the other hand, Software Defined Network (SDN) architecture improves flexibility and makes the IoT respond appropriately to the heterogeneity. This article proposes an SDN-based efficient clustering scheme for IoT using the Improved Sailfish optimization (ISFO) algorithm. In the proposed model, clustering of IoT devices is performed using the ISFO model and the model is installed on the SDN controller to manage the Cluster Head (CH) nodes of IoT devices. The performance evaluation of the proposed model was performed based on two scenarios with 150 and 300 nodes. The results show that for 150 nodes ISFO model in comparison with LEACH, LEACH-E reduced energy consumption by about 21.42% and 17.28%. For 300 ISFO nodes compared to LEACH, LEACH-E reduced energy consumption by about 37.84% and 27.23%. PeerJ Inc. 2023-07-10 /pmc/articles/PMC10403188/ /pubmed/37547416 http://dx.doi.org/10.7717/peerj-cs.1424 Text en ©2023 Mohammadi et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Artificial Intelligence
Mohammadi, Ramin
Akleylek, Sedat
Ghaffari, Ali
SDN-IoT: SDN-based efficient clustering scheme for IoT using improved Sailfish optimization algorithm
title SDN-IoT: SDN-based efficient clustering scheme for IoT using improved Sailfish optimization algorithm
title_full SDN-IoT: SDN-based efficient clustering scheme for IoT using improved Sailfish optimization algorithm
title_fullStr SDN-IoT: SDN-based efficient clustering scheme for IoT using improved Sailfish optimization algorithm
title_full_unstemmed SDN-IoT: SDN-based efficient clustering scheme for IoT using improved Sailfish optimization algorithm
title_short SDN-IoT: SDN-based efficient clustering scheme for IoT using improved Sailfish optimization algorithm
title_sort sdn-iot: sdn-based efficient clustering scheme for iot using improved sailfish optimization algorithm
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403188/
https://www.ncbi.nlm.nih.gov/pubmed/37547416
http://dx.doi.org/10.7717/peerj-cs.1424
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