Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • apa.csl
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Energy-efficient workflow scheduling with budget-deadline constraints for cloud
University of Tabriz, IRN.
University of Tabriz, IRN.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-9194-010X
2022 (English)In: Computing, ISSN 0010-485X, E-ISSN 1436-5057, Vol. 104, no 3, p. 601-625Article in journal (Refereed) Published
Abstract [en]

Cloud computing has become a well-known platform for solving big data and complex problems such as workflow applications. Infrastructure as a Service (IaaS) from the cloud is a suitable platform to solve these problems as it can potentially provide a nearly unlimited amount of resources using virtualization technology with a pay-per-use cost model. Various Quality of Service (QoS) objectives, such as cost and time, have been considered individually for workflow scheduling. In this paper, we proposed two energy-efficient heuristic algorithms with budget-deadline constraints that are appropriate for resources with Dynamic Voltage and Frequency Scaling (DVFS) enabled, as well as those that do not support DVFS. They are Budget Deadline Constrained Energy-aware (BDCE) and Budget Deadline DVFS-enabled energy-aware (BDD) algorithms for the cloud. Furthermore, they acquire affordable cost, faster scheduling length, and higher energy-saving ratio. Various evaluation metrics like success rate, cost and time ratios, energy consumption, utilization rate, and energy-saving ratio are utilized to evaluate the performance of the proposed algorithms. The obtained results are compared with budget-deadline constraints methods, such as BDSD, DBCS, and BDHEFT, as well as two other energy-efficient deadline-constrained algorithms, namely, ERES and Safari's algorithm in various scenarios on scientific workflow applications.

Place, publisher, year, edition, pages
Springer, 2022. Vol. 104, no 3, p. 601-625
Keywords [en]
Workflow scheduling, Energy, Deadline, Budget, Cloud computing
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-88242DOI: 10.1007/s00607-021-01030-9ISI: 000741913100001OAI: oai:DiVA.org:kau-88242DiVA, id: diva2:1634866
Available from: 2022-02-03 Created: 2022-02-03 Last updated: 2022-04-21Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records

Taheri, Javid

Search in DiVA

By author/editor
Taheri, Javid
By organisation
Department of Mathematics and Computer Science (from 2013)
In the same journal
Computing
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 171 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • apa.csl
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf