A Hybrid Optimization Approach for Edge Servers and Cloud Centers in Agricultural IoT.
Saved in:
| Title: | A Hybrid Optimization Approach for Edge Servers and Cloud Centers in Agricultural IoT. |
|---|---|
| Authors: | Wang, Yan1 2256678418@qq.com, Hu, Lijuan2 1023236794@qq.com, Liu, Chengzhi2 it-rocket@163.com |
| Source: | IAENG International Journal of Computer Science. May2026, Vol. 53 Issue 5, p1815-1822. 8p. |
| Subjects: | Data centers, Optimization algorithms, Clustering algorithms, Internet of things, Greedy algorithms, Communication infrastructure, Metaheuristic algorithms |
| Abstract: | This paper proposes an integrated algorithm to optimize the deployment of edge servers and cloud data centers in agricultural Internet of Things (IoT) networks. First, the K-medoids algorithm is employed to cluster data collection terminals and thereby initialize edge-server locations. A greedy algorithm with local refinement is then used to supplement coverage in previously uncovered areas. Subsequently, a gravitational search algorithm optimizes global server placement. The method achieves near-optimal deployment while guaranteeing full coverage. Real-world constraints are also incorporated by modeling forbidden zones, such as lakes, roads, and restricted areas, that must be avoided during infrastructure placement. [ABSTRACT FROM AUTHOR] |
| Copyright of IAENG International Journal of Computer Science is the property of International Association of Engineers (IAENG) 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 |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 193482036 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: A Hybrid Optimization Approach for Edge Servers and Cloud Centers in Agricultural IoT. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wang%2C+Yan%22">Wang, Yan</searchLink><relatesTo>1</relatesTo><i> 2256678418@qq.com</i><br /><searchLink fieldCode="AR" term="%22Hu%2C+Lijuan%22">Hu, Lijuan</searchLink><relatesTo>2</relatesTo><i> 1023236794@qq.com</i><br /><searchLink fieldCode="AR" term="%22Liu%2C+Chengzhi%22">Liu, Chengzhi</searchLink><relatesTo>2</relatesTo><i> it-rocket@163.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IAENG+International+Journal+of+Computer+Science%22">IAENG International Journal of Computer Science</searchLink>. May2026, Vol. 53 Issue 5, p1815-1822. 8p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Data+centers%22">Data centers</searchLink><br /><searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Clustering+algorithms%22">Clustering algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+of+things%22">Internet of things</searchLink><br /><searchLink fieldCode="DE" term="%22Greedy+algorithms%22">Greedy algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Communication+infrastructure%22">Communication infrastructure</searchLink><br /><searchLink fieldCode="DE" term="%22Metaheuristic+algorithms%22">Metaheuristic algorithms</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper proposes an integrated algorithm to optimize the deployment of edge servers and cloud data centers in agricultural Internet of Things (IoT) networks. First, the K-medoids algorithm is employed to cluster data collection terminals and thereby initialize edge-server locations. A greedy algorithm with local refinement is then used to supplement coverage in previously uncovered areas. Subsequently, a gravitational search algorithm optimizes global server placement. The method achieves near-optimal deployment while guaranteeing full coverage. Real-world constraints are also incorporated by modeling forbidden zones, such as lakes, roads, and restricted areas, that must be avoided during infrastructure placement. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IAENG International Journal of Computer Science is the property of International Association of Engineers (IAENG) 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=193482036 |
| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 8 StartPage: 1815 Subjects: – SubjectFull: Data centers Type: general – SubjectFull: Optimization algorithms Type: general – SubjectFull: Clustering algorithms Type: general – SubjectFull: Internet of things Type: general – SubjectFull: Greedy algorithms Type: general – SubjectFull: Communication infrastructure Type: general – SubjectFull: Metaheuristic algorithms Type: general Titles: – TitleFull: A Hybrid Optimization Approach for Edge Servers and Cloud Centers in Agricultural IoT. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wang, Yan – PersonEntity: Name: NameFull: Hu, Lijuan – PersonEntity: Name: NameFull: Liu, Chengzhi IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 1819656X Numbering: – Type: volume Value: 53 – Type: issue Value: 5 Titles: – TitleFull: IAENG International Journal of Computer Science Type: main |
| ResultId | 1 |
