A Hybrid Algorithm for Multi-Objective Scientific Workflow Scheduling in IaaS Cloud Article Swipe
Yongqiang Gao
,
Shuyun Zhang
,
Jiantao Zhou
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1109/access.2019.2939294
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1109/access.2019.2939294
With the increase in deployment of scientific workflow applications on an IaaS cloud computing environment, the distribution of workflow tasks to particular cloud instances to decrease runtime and cost has emerged as an important challenge. The cloud workflow scheduling is a well-known NP-hard problem. In this paper, we propose a new approach for multi-objective workflow scheduling in IaaS clouds offering a limited amount of instances and a flexible combination of instance types, and present a hybrid algorithm combining genetic algorithm, artificial bee colony optimization and decoding heuristic for scheduling workflow tasks over the available cloud resources while trying to optimize the workflow makespan and cost simultaneously. The proposed algorithm is evaluated for real-world scientific applications by a simulation process. The simulation results show that our proposed scheduling algorithm performs better than the current state-of-the-art algorithms. We validate the results by the Wilcoxon signed-rank test.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2019.2939294
- https://ieeexplore.ieee.org/ielx7/6287639/8600701/08822925.pdf
- OA Status
- gold
- Cited By
- 42
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2971411751
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2971411751Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/access.2019.2939294Digital Object Identifier
- Title
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A Hybrid Algorithm for Multi-Objective Scientific Workflow Scheduling in IaaS CloudWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2019Year of publication
- Publication date
-
2019-01-01Full publication date if available
- Authors
-
Yongqiang Gao, Shuyun Zhang, Jiantao ZhouList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2019.2939294Publisher landing page
- PDF URL
-
https://ieeexplore.ieee.org/ielx7/6287639/8600701/08822925.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://ieeexplore.ieee.org/ielx7/6287639/8600701/08822925.pdfDirect OA link when available
- Concepts
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Computer science, Workflow, Cloud computing, Distributed computing, Job shop scheduling, Scheduling (production processes), Workflow management system, Algorithm, Database, Operating system, Mathematical optimization, Schedule, MathematicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
42Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3, 2024: 8, 2023: 12, 2022: 9, 2021: 8Per-year citation counts (last 5 years)
- References (count)
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34Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.colony | 82 |
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| abstract_inverted_index.genetic | 78 |
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| abstract_inverted_index.Wilcoxon | 141 |
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| abstract_inverted_index.decoding | 85 |
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| abstract_inverted_index.state-of-the-art | 133 |
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| cited_by_percentile_year.min | 94 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.5699999928474426 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.96781637 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |