Job scheduling and dynamic data replication in data grid environment.
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| Title: | Job scheduling and dynamic data replication in data grid environment. |
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| Authors: | Mansouri, Najme1 najme.mansouri@gmail.com, Dastghaibyfard, Gholam1 |
| Source: | Journal of Supercomputing. Apr2013, Vol. 64 Issue 1, p204-225. 22p. |
| Subjects: | Data replication, Backup processing alternatives in electronic data processing, Algorithms, Algebra, Foundations of arithmetic |
| Abstract: | Data Grid is a geographically distributed environment that deals with large-scale data-intensive applications. Effective scheduling in Grid can reduce the amount of data transferred among nodes by submitting a job to a node, where most of the requested data files are available. Data replication is another key optimization technique for reducing access latency and managing large data by storing data in a wisely manner. In this paper, two algorithms are proposed: first, a novel job scheduling algorithm called Combined Scheduling Strategy (CSS) that considers the number of jobs waiting in queue, the location of required data for the job, and computational capability; second, a dynamic data replication strategy called Dynamic Hierarchical Replication Algorithm (DHRA) that improves file access time. DHRA stores each replica in an appropriate site, i.e., appropriate site in the requested region that has the highest number of access for that particular replica. Also, it can minimize access latency by selecting the best replica when various sites hold replicas of datasets. The simulation results demonstrate the proposed replication and scheduling strategies give better performance compared to the other algorithms. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Supercomputing is the property of Springer Nature 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 |
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| Header | DbId: egs DbLabel: Engineering Source An: 86170140 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Job scheduling and dynamic data replication in data grid environment. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mansouri%2C+Najme%22">Mansouri, Najme</searchLink><relatesTo>1</relatesTo><i> najme.mansouri@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Dastghaibyfard%2C+Gholam%22">Dastghaibyfard, Gholam</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Supercomputing%22">Journal of Supercomputing</searchLink>. Apr2013, Vol. 64 Issue 1, p204-225. 22p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Data+replication%22">Data replication</searchLink><br /><searchLink fieldCode="DE" term="%22Backup+processing+alternatives+in+electronic+data+processing%22">Backup processing alternatives in electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Algebra%22">Algebra</searchLink><br /><searchLink fieldCode="DE" term="%22Foundations+of+arithmetic%22">Foundations of arithmetic</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Data Grid is a geographically distributed environment that deals with large-scale data-intensive applications. Effective scheduling in Grid can reduce the amount of data transferred among nodes by submitting a job to a node, where most of the requested data files are available. Data replication is another key optimization technique for reducing access latency and managing large data by storing data in a wisely manner. In this paper, two algorithms are proposed: first, a novel job scheduling algorithm called Combined Scheduling Strategy (CSS) that considers the number of jobs waiting in queue, the location of required data for the job, and computational capability; second, a dynamic data replication strategy called Dynamic Hierarchical Replication Algorithm (DHRA) that improves file access time. DHRA stores each replica in an appropriate site, i.e., appropriate site in the requested region that has the highest number of access for that particular replica. Also, it can minimize access latency by selecting the best replica when various sites hold replicas of datasets. The simulation results demonstrate the proposed replication and scheduling strategies give better performance compared to the other algorithms. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Supercomputing is the property of Springer Nature 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: 10.1007/s11227-012-0850-2 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 204 Subjects: – SubjectFull: Data replication Type: general – SubjectFull: Backup processing alternatives in electronic data processing Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Algebra Type: general – SubjectFull: Foundations of arithmetic Type: general Titles: – TitleFull: Job scheduling and dynamic data replication in data grid environment. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mansouri, Najme – PersonEntity: Name: NameFull: Dastghaibyfard, Gholam IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2013 Type: published Y: 2013 Identifiers: – Type: issn-print Value: 09208542 Numbering: – Type: volume Value: 64 – Type: issue Value: 1 Titles: – TitleFull: Journal of Supercomputing Type: main |
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