An online parallel scheduling method with application to energy-efficiency in cloud computing.
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| Title: | An online parallel scheduling method with application to energy-efficiency in cloud computing. |
|---|---|
| Authors: | Tian, Wenhong1 tian_wenhong@uestc.edu.cn, Xiong, Qin1, Cao, Jun1 |
| Source: | Journal of Supercomputing. Dec2013, Vol. 66 Issue 3, p1773-1790. 18p. |
| Subjects: | Parallel scheduling (Computer scheduling), Application software, Energy consumption, Cloud computing, Virtual machine systems, Constraint satisfaction |
| Abstract: | This paper considers online energy-efficient scheduling of virtual machines (VMs) for Cloud data centers. Each request is associated with a start-time, an end-time, a processing time and a capacity demand from a Physical Machine (PM). The goal is to schedule all of the requests non-preemptively in their start-time-end-time windows, subjecting to PM capacity constraints, such that the total busy time of all used PMs is minimized (called MinTBT-ON for abbreviation). This problem is a fundamental scheduling problem for parallel jobs allocation on multiple machines; it has important applications in power-aware scheduling in cloud computing, optical network design, customer service systems, and other related areas. Offline scheduling to minimize busy time is NP-hard already in the special case where all jobs have the same processing time and can be scheduled in a fixed time interval. One best-known result for MinTBT-ON problem is a g-competitive algorithm for general instances and unit-size jobs using First-Fit algorithm where g is the total capacity of a machine. In this paper, a $(1+\frac{g-2}{k}-\frac{g-1}{k^{2}})$ -competitive algorithm, Dynamic Bipartition-First-Fit (BFF) is proposed and proved for general case, where k is the ratio of the length of the longest interval over the length of the second longest interval for k>1 and g≥2. More results in general and special cases are obtained to improve the best-known bounds. [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 |
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| Items | – Name: Title Label: Title Group: Ti Data: An online parallel scheduling method with application to energy-efficiency in cloud computing. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Tian%2C+Wenhong%22">Tian, Wenhong</searchLink><relatesTo>1</relatesTo><i> tian_wenhong@uestc.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Xiong%2C+Qin%22">Xiong, Qin</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Cao%2C+Jun%22">Cao, Jun</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Supercomputing%22">Journal of Supercomputing</searchLink>. Dec2013, Vol. 66 Issue 3, p1773-1790. 18p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Parallel+scheduling+%28Computer+scheduling%29%22">Parallel scheduling (Computer scheduling)</searchLink><br /><searchLink fieldCode="DE" term="%22Application+software%22">Application software</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Cloud+computing%22">Cloud computing</searchLink><br /><searchLink fieldCode="DE" term="%22Virtual+machine+systems%22">Virtual machine systems</searchLink><br /><searchLink fieldCode="DE" term="%22Constraint+satisfaction%22">Constraint satisfaction</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper considers online energy-efficient scheduling of virtual machines (VMs) for Cloud data centers. Each request is associated with a start-time, an end-time, a processing time and a capacity demand from a Physical Machine (PM). The goal is to schedule all of the requests non-preemptively in their start-time-end-time windows, subjecting to PM capacity constraints, such that the total busy time of all used PMs is minimized (called MinTBT-ON for abbreviation). This problem is a fundamental scheduling problem for parallel jobs allocation on multiple machines; it has important applications in power-aware scheduling in cloud computing, optical network design, customer service systems, and other related areas. Offline scheduling to minimize busy time is NP-hard already in the special case where all jobs have the same processing time and can be scheduled in a fixed time interval. One best-known result for MinTBT-ON problem is a g-competitive algorithm for general instances and unit-size jobs using First-Fit algorithm where g is the total capacity of a machine. In this paper, a $(1+\frac{g-2}{k}-\frac{g-1}{k^{2}})$ -competitive algorithm, Dynamic Bipartition-First-Fit (BFF) is proposed and proved for general case, where k is the ratio of the length of the longest interval over the length of the second longest interval for k>1 and g≥2. More results in general and special cases are obtained to improve the best-known bounds. [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/s11227-013-0974-z Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 1773 Subjects: – SubjectFull: Parallel scheduling (Computer scheduling) Type: general – SubjectFull: Application software Type: general – SubjectFull: Energy consumption Type: general – SubjectFull: Cloud computing Type: general – SubjectFull: Virtual machine systems Type: general – SubjectFull: Constraint satisfaction Type: general Titles: – TitleFull: An online parallel scheduling method with application to energy-efficiency in cloud computing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Tian, Wenhong – PersonEntity: Name: NameFull: Xiong, Qin – PersonEntity: Name: NameFull: Cao, Jun IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2013 Type: published Y: 2013 Identifiers: – Type: issn-print Value: 09208542 Numbering: – Type: volume Value: 66 – Type: issue Value: 3 Titles: – TitleFull: Journal of Supercomputing Type: main |
| ResultId | 1 |
