A Hybrid Algorithm for Multi-Objective Scientific Workflow Scheduling in IaaS Cloud
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 probl...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8822925/ |
| _version_ | 1818910239477465088 |
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| author | Yongqiang Gao Shuyun Zhang Jiantao Zhou |
| author_facet | Yongqiang Gao Shuyun Zhang Jiantao Zhou |
| author_sort | Yongqiang Gao |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-19T22:39:39Z |
| format | Article |
| id | doaj.art-1a69eeb7e03b4ab9bd5d79828b65ee84 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T22:39:39Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-1a69eeb7e03b4ab9bd5d79828b65ee842022-12-21T20:03:07ZengIEEEIEEE Access2169-35362019-01-01712578312579510.1109/ACCESS.2019.29392948822925A Hybrid Algorithm for Multi-Objective Scientific Workflow Scheduling in IaaS CloudYongqiang Gao0https://orcid.org/0000-0003-3273-3148Shuyun Zhang1Jiantao Zhou2College of Computer Science, Inner Mongolia University, Hohhot, ChinaCollege of Computer Science, Inner Mongolia University, Hohhot, ChinaCollege of Computer Science, Inner Mongolia University, Hohhot, ChinaWith 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.https://ieeexplore.ieee.org/document/8822925/Cloud computingmulti-objective optimizationworkflow schedule |
| spellingShingle | Yongqiang Gao Shuyun Zhang Jiantao Zhou A Hybrid Algorithm for Multi-Objective Scientific Workflow Scheduling in IaaS Cloud IEEE Access Cloud computing multi-objective optimization workflow schedule |
| title | A Hybrid Algorithm for Multi-Objective Scientific Workflow Scheduling in IaaS Cloud |
| title_full | A Hybrid Algorithm for Multi-Objective Scientific Workflow Scheduling in IaaS Cloud |
| title_fullStr | A Hybrid Algorithm for Multi-Objective Scientific Workflow Scheduling in IaaS Cloud |
| title_full_unstemmed | A Hybrid Algorithm for Multi-Objective Scientific Workflow Scheduling in IaaS Cloud |
| title_short | A Hybrid Algorithm for Multi-Objective Scientific Workflow Scheduling in IaaS Cloud |
| title_sort | hybrid algorithm for multi objective scientific workflow scheduling in iaas cloud |
| topic | Cloud computing multi-objective optimization workflow schedule |
| url | https://ieeexplore.ieee.org/document/8822925/ |
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