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IoT Adaptive Dynamic Blockchain Networking Method Based on Discrete Heartbeat Signals

The combination of blockchain technology and Internet of Things (IoT) technology has brought many significant advantages and new development directions. With the development of embedded technology and 5G communication technology, the performance limitations and network limitations that are tradition...

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Autores principales: Hu, Xueyang, Zheng, Yili, Su, Yu, Guo, Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7697744/
https://www.ncbi.nlm.nih.gov/pubmed/33202552
http://dx.doi.org/10.3390/s20226503
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author Hu, Xueyang
Zheng, Yili
Su, Yu
Guo, Rui
author_facet Hu, Xueyang
Zheng, Yili
Su, Yu
Guo, Rui
author_sort Hu, Xueyang
collection PubMed
description The combination of blockchain technology and Internet of Things (IoT) technology has brought many significant advantages and new development directions. With the development of embedded technology and 5G communication technology, the performance limitations and network limitations that are traditionally believed to restrict the application of blockchain technology to IoT devices have been broken. The development of “blockchain + 5G + IoT” provides reliable data from the source for the blockchain, linking the credible mapping of physical assets and digital assets. However, at the beginning of the blockchain design, the application of the IoT was not fully considered, so there have been some obvious defects in applying the blockchain technology in the IoT. In the Byzantine fault tolerance (BFT) consensus algorithm of traditional blockchain, the entire blockchain network will become paralyzed when more than 1/3 of the nodes in the network are offline. However, in IoT applications, this situation is likely to occur and greatly limits the security and stability of the application of blockchain technology in the IoT. In order to solve this problem, we proposed an IoT adaptive dynamic blockchain networking method based on discrete heartbeat signals. The feature of the method is to set a different monitoring time for each group of nodes, that is, discrete heartbeat signals monitoring. When the number of nodes gradually decreases, the IoT adaptive dynamic blockchain network can dynamically adapt to this process. Even when more than 1/3 of the IoT are offline, the adaptive dynamic IoT blockchain network can maintain stable running. This method also has the advantages of a short network expectation recovery time and avoids instantaneous system paralysis caused by the thundering herd effect. This research improves the security and stability of the application of blockchain technology in the IoT, and provides the necessary technical foundation for the better combination of blockchain technology and IoT technology.
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spelling pubmed-76977442020-11-29 IoT Adaptive Dynamic Blockchain Networking Method Based on Discrete Heartbeat Signals Hu, Xueyang Zheng, Yili Su, Yu Guo, Rui Sensors (Basel) Article The combination of blockchain technology and Internet of Things (IoT) technology has brought many significant advantages and new development directions. With the development of embedded technology and 5G communication technology, the performance limitations and network limitations that are traditionally believed to restrict the application of blockchain technology to IoT devices have been broken. The development of “blockchain + 5G + IoT” provides reliable data from the source for the blockchain, linking the credible mapping of physical assets and digital assets. However, at the beginning of the blockchain design, the application of the IoT was not fully considered, so there have been some obvious defects in applying the blockchain technology in the IoT. In the Byzantine fault tolerance (BFT) consensus algorithm of traditional blockchain, the entire blockchain network will become paralyzed when more than 1/3 of the nodes in the network are offline. However, in IoT applications, this situation is likely to occur and greatly limits the security and stability of the application of blockchain technology in the IoT. In order to solve this problem, we proposed an IoT adaptive dynamic blockchain networking method based on discrete heartbeat signals. The feature of the method is to set a different monitoring time for each group of nodes, that is, discrete heartbeat signals monitoring. When the number of nodes gradually decreases, the IoT adaptive dynamic blockchain network can dynamically adapt to this process. Even when more than 1/3 of the IoT are offline, the adaptive dynamic IoT blockchain network can maintain stable running. This method also has the advantages of a short network expectation recovery time and avoids instantaneous system paralysis caused by the thundering herd effect. This research improves the security and stability of the application of blockchain technology in the IoT, and provides the necessary technical foundation for the better combination of blockchain technology and IoT technology. MDPI 2020-11-14 /pmc/articles/PMC7697744/ /pubmed/33202552 http://dx.doi.org/10.3390/s20226503 Text en © 2020 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
Hu, Xueyang
Zheng, Yili
Su, Yu
Guo, Rui
IoT Adaptive Dynamic Blockchain Networking Method Based on Discrete Heartbeat Signals
title IoT Adaptive Dynamic Blockchain Networking Method Based on Discrete Heartbeat Signals
title_full IoT Adaptive Dynamic Blockchain Networking Method Based on Discrete Heartbeat Signals
title_fullStr IoT Adaptive Dynamic Blockchain Networking Method Based on Discrete Heartbeat Signals
title_full_unstemmed IoT Adaptive Dynamic Blockchain Networking Method Based on Discrete Heartbeat Signals
title_short IoT Adaptive Dynamic Blockchain Networking Method Based on Discrete Heartbeat Signals
title_sort iot adaptive dynamic blockchain networking method based on discrete heartbeat signals
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7697744/
https://www.ncbi.nlm.nih.gov/pubmed/33202552
http://dx.doi.org/10.3390/s20226503
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