Optimizing energy‐efficient data replication for IoT applications in fog computing.
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| Title: | Optimizing energy‐efficient data replication for IoT applications in fog computing. |
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| Authors: | Mohamed, Ahmed Awad1 (AUTHOR), Diabat, Ali2,3,4 (AUTHOR), Abualigah, Laith5,6,7,8 (AUTHOR) aligah.2020@gmail.com |
| Source: | International Journal of Communication Systems. 9/25/2024, Vol. 37 Issue 14, p1-18. 18p. |
| Subjects: | Data replication, Carbon emissions, Electronic data processing, Internet of things, Communication infrastructure |
| Abstract: | Summary: The rise of the Internet of Things (IoT) has given rise to an era marked by interconnected devices and substantial data generation. This has led to an increased reliance on cloud computing for data processing and storage, primarily due to its cost‐effective pay‐for‐use model. However, this dependence has prompted critical inquiries into the optimal replication of data: what data to replicate, when to replicate it, and where to place new replicas strategically. Conventional cloud data replication often results in resource overutilization, performance bottlenecks, increased workloads, energy consumption, prolonged user wait times, and suboptimal response times. In response to these challenges, this paper introduces a novel approach named Multiobjective Optimization Harris Hawks Optimization with Salp Swarm Algorithm (MOHHOSSA). This approach employs multiobjective optimization (MOO) alongside Harris Hawks Optimization (HHO) and IoT‐based Salp Swarm Algorithm (SSA) for cloud computing environments. MOHHOSSA efficiently identifies data replication opportunities and strategically allocates them across nodes in cloud computing infrastructures. The algorithm aims to enhance key performance metrics, including energy consumption, carbon dioxide emission rate, and mean service time. Extensive experimental validation demonstrates MOHHOSSA's superior performance compared to alternative algorithms. It excels in optimizing energy efficiency, load distribution, mean service time, and the establishment of cost‐effective communication paths between nodes. This research represents a significant advancement in addressing challenges related to IoT data replication in cloud computing, ultimately promoting more sustainable, efficient, and responsive cloud‐based services. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Communication Systems is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 178974180 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Optimizing energy‐efficient data replication for IoT applications in fog computing. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mohamed%2C+Ahmed+Awad%22">Mohamed, Ahmed Awad</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Diabat%2C+Ali%22">Diabat, Ali</searchLink><relatesTo>2,3,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Abualigah%2C+Laith%22">Abualigah, Laith</searchLink><relatesTo>5,6,7,8</relatesTo> (AUTHOR)<i> aligah.2020@gmail.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Communication+Systems%22">International Journal of Communication Systems</searchLink>. 9/25/2024, Vol. 37 Issue 14, p1-18. 18p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Data+replication%22">Data replication</searchLink><br /><searchLink fieldCode="DE" term="%22Carbon+emissions%22">Carbon emissions</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+of+things%22">Internet of things</searchLink><br /><searchLink fieldCode="DE" term="%22Communication+infrastructure%22">Communication infrastructure</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Summary: The rise of the Internet of Things (IoT) has given rise to an era marked by interconnected devices and substantial data generation. This has led to an increased reliance on cloud computing for data processing and storage, primarily due to its cost‐effective pay‐for‐use model. However, this dependence has prompted critical inquiries into the optimal replication of data: what data to replicate, when to replicate it, and where to place new replicas strategically. Conventional cloud data replication often results in resource overutilization, performance bottlenecks, increased workloads, energy consumption, prolonged user wait times, and suboptimal response times. In response to these challenges, this paper introduces a novel approach named Multiobjective Optimization Harris Hawks Optimization with Salp Swarm Algorithm (MOHHOSSA). This approach employs multiobjective optimization (MOO) alongside Harris Hawks Optimization (HHO) and IoT‐based Salp Swarm Algorithm (SSA) for cloud computing environments. MOHHOSSA efficiently identifies data replication opportunities and strategically allocates them across nodes in cloud computing infrastructures. The algorithm aims to enhance key performance metrics, including energy consumption, carbon dioxide emission rate, and mean service time. Extensive experimental validation demonstrates MOHHOSSA's superior performance compared to alternative algorithms. It excels in optimizing energy efficiency, load distribution, mean service time, and the establishment of cost‐effective communication paths between nodes. This research represents a significant advancement in addressing challenges related to IoT data replication in cloud computing, ultimately promoting more sustainable, efficient, and responsive cloud‐based services. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Communication Systems is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/dac.5864 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 1 Subjects: – SubjectFull: Data replication Type: general – SubjectFull: Carbon emissions Type: general – SubjectFull: Electronic data processing Type: general – SubjectFull: Internet of things Type: general – SubjectFull: Communication infrastructure Type: general Titles: – TitleFull: Optimizing energy‐efficient data replication for IoT applications in fog computing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mohamed, Ahmed Awad – PersonEntity: Name: NameFull: Diabat, Ali – PersonEntity: Name: NameFull: Abualigah, Laith IsPartOfRelationships: – BibEntity: Dates: – D: 25 M: 09 Text: 9/25/2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 10745351 Numbering: – Type: volume Value: 37 – Type: issue Value: 14 Titles: – TitleFull: International Journal of Communication Systems Type: main |
| ResultId | 1 |
