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A Multi-Hop Clustering Mechanism for Scalable IoT Networks

It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet with an individual connection may fac...

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Autores principales: Sung, Yoonyoung, Lee, Sookyoung, Lee, Meejeong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5948489/
https://www.ncbi.nlm.nih.gov/pubmed/29570691
http://dx.doi.org/10.3390/s18040961
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author Sung, Yoonyoung
Lee, Sookyoung
Lee, Meejeong
author_facet Sung, Yoonyoung
Lee, Sookyoung
Lee, Meejeong
author_sort Sung, Yoonyoung
collection PubMed
description It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet with an individual connection may face serious scalability issues. The scalability problem of the IoT network may be alleviated by grouping the nodes of the IoT network into clusters and having a representative node in each cluster connect to the Internet on behalf of the other nodes in the cluster instead of having a per-node Internet connection and communication. In this paper, we propose a multi-hop clustering mechanism for IoT networks to minimize the number of required Internet connections. Specifically, the objective of proposed mechanism is to select the minimum number of coordinators, which take the role of a representative node for the cluster, i.e., having the Internet connection on behalf of the rest of the nodes in the cluster and to map a partition of the IoT nodes onto the selected set of coordinators to minimize the total distance between the nodes and their respective coordinator under a certain constraint in terms of maximum hop count between the IoT nodes and their respective coordinator. Since this problem can be mapped into a set cover problem which is known as NP-hard, we pursue a heuristic approach to solve the problem and analyze the complexity of the proposed solution. Through a set of experiments with varying parameters, the proposed scheme shows 63–87.3% reduction of the Internet connections depending on the number of the IoT nodes while that of the optimal solution is 65.6–89.9% in a small scale network. Moreover, it is shown that the performance characteristics of the proposed mechanism coincide with expected performance characteristics of the optimal solution in a large-scale network.
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spelling pubmed-59484892018-05-17 A Multi-Hop Clustering Mechanism for Scalable IoT Networks Sung, Yoonyoung Lee, Sookyoung Lee, Meejeong Sensors (Basel) Article It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet with an individual connection may face serious scalability issues. The scalability problem of the IoT network may be alleviated by grouping the nodes of the IoT network into clusters and having a representative node in each cluster connect to the Internet on behalf of the other nodes in the cluster instead of having a per-node Internet connection and communication. In this paper, we propose a multi-hop clustering mechanism for IoT networks to minimize the number of required Internet connections. Specifically, the objective of proposed mechanism is to select the minimum number of coordinators, which take the role of a representative node for the cluster, i.e., having the Internet connection on behalf of the rest of the nodes in the cluster and to map a partition of the IoT nodes onto the selected set of coordinators to minimize the total distance between the nodes and their respective coordinator under a certain constraint in terms of maximum hop count between the IoT nodes and their respective coordinator. Since this problem can be mapped into a set cover problem which is known as NP-hard, we pursue a heuristic approach to solve the problem and analyze the complexity of the proposed solution. Through a set of experiments with varying parameters, the proposed scheme shows 63–87.3% reduction of the Internet connections depending on the number of the IoT nodes while that of the optimal solution is 65.6–89.9% in a small scale network. Moreover, it is shown that the performance characteristics of the proposed mechanism coincide with expected performance characteristics of the optimal solution in a large-scale network. MDPI 2018-03-23 /pmc/articles/PMC5948489/ /pubmed/29570691 http://dx.doi.org/10.3390/s18040961 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sung, Yoonyoung
Lee, Sookyoung
Lee, Meejeong
A Multi-Hop Clustering Mechanism for Scalable IoT Networks
title A Multi-Hop Clustering Mechanism for Scalable IoT Networks
title_full A Multi-Hop Clustering Mechanism for Scalable IoT Networks
title_fullStr A Multi-Hop Clustering Mechanism for Scalable IoT Networks
title_full_unstemmed A Multi-Hop Clustering Mechanism for Scalable IoT Networks
title_short A Multi-Hop Clustering Mechanism for Scalable IoT Networks
title_sort multi-hop clustering mechanism for scalable iot networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5948489/
https://www.ncbi.nlm.nih.gov/pubmed/29570691
http://dx.doi.org/10.3390/s18040961
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