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Replica selection and placement techniques on the IoT and edge computing: a deep study
Internet of Things (IoT) has lately been presented as a new technological transformation in which things are connected via the Internet. Several sensors and devices create data and send vital signals constantly over sophisticated networks that allow machine-to-machine interactions and monitor and ma...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444506/ http://dx.doi.org/10.1007/s11276-021-02793-x |
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author | Shao, Zhong-Liang Huang, Cheng Li, Heng |
author_facet | Shao, Zhong-Liang Huang, Cheng Li, Heng |
author_sort | Shao, Zhong-Liang |
collection | PubMed |
description | Internet of Things (IoT) has lately been presented as a new technological transformation in which things are connected via the Internet. Several sensors and devices create data and send vital signals constantly over sophisticated networks that allow machine-to-machine interactions and monitor and manage key smart-world infrastructures. Since huge amounts of data are generated, reducing the data access costs is a critical issue. Edge computing has been developed as a novel paradigm for solving IoT demands to reduce the rise in resource congestion. One of the most significant data management challenges in the IoT is selecting suitable replication things that minimize reaction time and cost. Therefore, our goal is to examine replica selection and placement techniques in IoT and edge computing. The findings revealed that the edge computing environment might significantly enhance system performance regarding access response time, prediction accuracy, effective network, and increased data availability. Furthermore, the results illustrate that data provenance is necessary to raise the accuracy of the data by. Also, the results showed that the most important challenge in data replication and placement techniques in IoT and edge computing was the availability of data and access response time. |
format | Online Article Text |
id | pubmed-8444506 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-84445062021-09-17 Replica selection and placement techniques on the IoT and edge computing: a deep study Shao, Zhong-Liang Huang, Cheng Li, Heng Wireless Netw Original Paper Internet of Things (IoT) has lately been presented as a new technological transformation in which things are connected via the Internet. Several sensors and devices create data and send vital signals constantly over sophisticated networks that allow machine-to-machine interactions and monitor and manage key smart-world infrastructures. Since huge amounts of data are generated, reducing the data access costs is a critical issue. Edge computing has been developed as a novel paradigm for solving IoT demands to reduce the rise in resource congestion. One of the most significant data management challenges in the IoT is selecting suitable replication things that minimize reaction time and cost. Therefore, our goal is to examine replica selection and placement techniques in IoT and edge computing. The findings revealed that the edge computing environment might significantly enhance system performance regarding access response time, prediction accuracy, effective network, and increased data availability. Furthermore, the results illustrate that data provenance is necessary to raise the accuracy of the data by. Also, the results showed that the most important challenge in data replication and placement techniques in IoT and edge computing was the availability of data and access response time. Springer US 2021-09-16 2021 /pmc/articles/PMC8444506/ http://dx.doi.org/10.1007/s11276-021-02793-x Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Paper Shao, Zhong-Liang Huang, Cheng Li, Heng Replica selection and placement techniques on the IoT and edge computing: a deep study |
title | Replica selection and placement techniques on the IoT and edge computing: a deep study |
title_full | Replica selection and placement techniques on the IoT and edge computing: a deep study |
title_fullStr | Replica selection and placement techniques on the IoT and edge computing: a deep study |
title_full_unstemmed | Replica selection and placement techniques on the IoT and edge computing: a deep study |
title_short | Replica selection and placement techniques on the IoT and edge computing: a deep study |
title_sort | replica selection and placement techniques on the iot and edge computing: a deep study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444506/ http://dx.doi.org/10.1007/s11276-021-02793-x |
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