Cargando…
An Overview of Fog Data Analytics for IoT Applications
With the rapid growth in the data and processing over the cloud, it has become easier to access those data. On the other hand, it poses many technical and security challenges to the users of those provisions. Fog computing makes these technical issues manageable to some extent. Fog computing is one...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824595/ https://www.ncbi.nlm.nih.gov/pubmed/36616797 http://dx.doi.org/10.3390/s23010199 |
_version_ | 1784866448816996352 |
---|---|
author | Bhatia, Jitendra Italiya, Kiran Jadeja, Kuldeepsinh Kumhar, Malaram Chauhan, Uttam Tanwar, Sudeep Bhavsar, Madhuri Sharma, Ravi Manea, Daniela Lucia Verdes, Marina Raboaca, Maria Simona |
author_facet | Bhatia, Jitendra Italiya, Kiran Jadeja, Kuldeepsinh Kumhar, Malaram Chauhan, Uttam Tanwar, Sudeep Bhavsar, Madhuri Sharma, Ravi Manea, Daniela Lucia Verdes, Marina Raboaca, Maria Simona |
author_sort | Bhatia, Jitendra |
collection | PubMed |
description | With the rapid growth in the data and processing over the cloud, it has become easier to access those data. On the other hand, it poses many technical and security challenges to the users of those provisions. Fog computing makes these technical issues manageable to some extent. Fog computing is one of the promising solutions for handling the big data produced by the IoT, which are often security-critical and time-sensitive. Massive IoT data analytics by a fog computing structure is emerging and requires extensive research for more proficient knowledge and smart decisions. Though an advancement in big data analytics is taking place, it does not consider fog data analytics. However, there are many challenges, including heterogeneity, security, accessibility, resource sharing, network communication overhead, the real-time data processing of complex data, etc. This paper explores various research challenges and their solution using the next-generation fog data analytics and IoT networks. We also performed an experimental analysis based on fog computing and cloud architecture. The result shows that fog computing outperforms the cloud in terms of network utilization and latency. Finally, the paper is concluded with future trends. |
format | Online Article Text |
id | pubmed-9824595 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98245952023-01-08 An Overview of Fog Data Analytics for IoT Applications Bhatia, Jitendra Italiya, Kiran Jadeja, Kuldeepsinh Kumhar, Malaram Chauhan, Uttam Tanwar, Sudeep Bhavsar, Madhuri Sharma, Ravi Manea, Daniela Lucia Verdes, Marina Raboaca, Maria Simona Sensors (Basel) Review With the rapid growth in the data and processing over the cloud, it has become easier to access those data. On the other hand, it poses many technical and security challenges to the users of those provisions. Fog computing makes these technical issues manageable to some extent. Fog computing is one of the promising solutions for handling the big data produced by the IoT, which are often security-critical and time-sensitive. Massive IoT data analytics by a fog computing structure is emerging and requires extensive research for more proficient knowledge and smart decisions. Though an advancement in big data analytics is taking place, it does not consider fog data analytics. However, there are many challenges, including heterogeneity, security, accessibility, resource sharing, network communication overhead, the real-time data processing of complex data, etc. This paper explores various research challenges and their solution using the next-generation fog data analytics and IoT networks. We also performed an experimental analysis based on fog computing and cloud architecture. The result shows that fog computing outperforms the cloud in terms of network utilization and latency. Finally, the paper is concluded with future trends. MDPI 2022-12-24 /pmc/articles/PMC9824595/ /pubmed/36616797 http://dx.doi.org/10.3390/s23010199 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Bhatia, Jitendra Italiya, Kiran Jadeja, Kuldeepsinh Kumhar, Malaram Chauhan, Uttam Tanwar, Sudeep Bhavsar, Madhuri Sharma, Ravi Manea, Daniela Lucia Verdes, Marina Raboaca, Maria Simona An Overview of Fog Data Analytics for IoT Applications |
title | An Overview of Fog Data Analytics for IoT Applications |
title_full | An Overview of Fog Data Analytics for IoT Applications |
title_fullStr | An Overview of Fog Data Analytics for IoT Applications |
title_full_unstemmed | An Overview of Fog Data Analytics for IoT Applications |
title_short | An Overview of Fog Data Analytics for IoT Applications |
title_sort | overview of fog data analytics for iot applications |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824595/ https://www.ncbi.nlm.nih.gov/pubmed/36616797 http://dx.doi.org/10.3390/s23010199 |
work_keys_str_mv | AT bhatiajitendra anoverviewoffogdataanalyticsforiotapplications AT italiyakiran anoverviewoffogdataanalyticsforiotapplications AT jadejakuldeepsinh anoverviewoffogdataanalyticsforiotapplications AT kumharmalaram anoverviewoffogdataanalyticsforiotapplications AT chauhanuttam anoverviewoffogdataanalyticsforiotapplications AT tanwarsudeep anoverviewoffogdataanalyticsforiotapplications AT bhavsarmadhuri anoverviewoffogdataanalyticsforiotapplications AT sharmaravi anoverviewoffogdataanalyticsforiotapplications AT maneadanielalucia anoverviewoffogdataanalyticsforiotapplications AT verdesmarina anoverviewoffogdataanalyticsforiotapplications AT raboacamariasimona anoverviewoffogdataanalyticsforiotapplications AT bhatiajitendra overviewoffogdataanalyticsforiotapplications AT italiyakiran overviewoffogdataanalyticsforiotapplications AT jadejakuldeepsinh overviewoffogdataanalyticsforiotapplications AT kumharmalaram overviewoffogdataanalyticsforiotapplications AT chauhanuttam overviewoffogdataanalyticsforiotapplications AT tanwarsudeep overviewoffogdataanalyticsforiotapplications AT bhavsarmadhuri overviewoffogdataanalyticsforiotapplications AT sharmaravi overviewoffogdataanalyticsforiotapplications AT maneadanielalucia overviewoffogdataanalyticsforiotapplications AT verdesmarina overviewoffogdataanalyticsforiotapplications AT raboacamariasimona overviewoffogdataanalyticsforiotapplications |