Cost Adaptive VM Management for Scientific Workflow Application in Mobile Cloud

Woo Joong Kim; Dong Ki Kang; Seong Hwan Kim; Chan Hyun Youn

doi:10.1007/s11036-015-0593-4

Cost Adaptive VM Management for Scientific Workflow Application in Mobile Cloud

Woo Joong Kim
, Dong Ki Kang
, Seong Hwan Kim
, Chan Hyun Youn^*

^*Corresponding author for this work

Department of Computer Science & Artificial Intelligence

Korea Advanced Institute of Science and Technology

Research output: Contribution to journal › Journal article › peer-review

11 Scopus citations

Abstract

In this paper, to guarantee Service Level Agreement composed of the deadline and budget given by users for workflow application services in mobile cloud, we propose the two-phases algorithm with a cost adaptive VM management. Firstly, the greedy based workflow co-scheduling phase schedules a workflow by using a resource consolidation in a parallel manner to decrease a cost with the deadline assurance. Secondly, the resource profiling based placement phase locates a VM to a certain physical host in the multi-cloud using the profile on the property of clouds in order to comply with the budget while maximizing the service quality. We implement mobile cloud brokering system with the two-phases algorithm and demonstrate that our proposed system outperforms traditional cloud systems through several experimental results.

Original language	English
Pages (from-to)	328-336
Number of pages	9
Journal	Mobile Networks and Applications
Volume	20
Issue number	3
DOIs	https://doi.org/10.1007/s11036-015-0593-4
State	Published - 2015.06.1

Keywords

Cost adaptive resource management
Mobile cloud brokering system
Mobile cloud computing

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10.1007/s11036-015-0593-4

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title = "Cost Adaptive VM Management for Scientific Workflow Application in Mobile Cloud",

abstract = "In this paper, to guarantee Service Level Agreement composed of the deadline and budget given by users for workflow application services in mobile cloud, we propose the two-phases algorithm with a cost adaptive VM management. Firstly, the greedy based workflow co-scheduling phase schedules a workflow by using a resource consolidation in a parallel manner to decrease a cost with the deadline assurance. Secondly, the resource profiling based placement phase locates a VM to a certain physical host in the multi-cloud using the profile on the property of clouds in order to comply with the budget while maximizing the service quality. We implement mobile cloud brokering system with the two-phases algorithm and demonstrate that our proposed system outperforms traditional cloud systems through several experimental results.",

keywords = "Cost adaptive resource management, Mobile cloud brokering system, Mobile cloud computing",

author = "Kim, \{Woo Joong\} and Kang, \{Dong Ki\} and Kim, \{Seong Hwan\} and Youn, \{Chan Hyun\}",

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AU - Kim, Woo Joong

AU - Kang, Dong Ki

AU - Kim, Seong Hwan

AU - Youn, Chan Hyun

PY - 2015/6/1

Y1 - 2015/6/1

N2 - In this paper, to guarantee Service Level Agreement composed of the deadline and budget given by users for workflow application services in mobile cloud, we propose the two-phases algorithm with a cost adaptive VM management. Firstly, the greedy based workflow co-scheduling phase schedules a workflow by using a resource consolidation in a parallel manner to decrease a cost with the deadline assurance. Secondly, the resource profiling based placement phase locates a VM to a certain physical host in the multi-cloud using the profile on the property of clouds in order to comply with the budget while maximizing the service quality. We implement mobile cloud brokering system with the two-phases algorithm and demonstrate that our proposed system outperforms traditional cloud systems through several experimental results.

AB - In this paper, to guarantee Service Level Agreement composed of the deadline and budget given by users for workflow application services in mobile cloud, we propose the two-phases algorithm with a cost adaptive VM management. Firstly, the greedy based workflow co-scheduling phase schedules a workflow by using a resource consolidation in a parallel manner to decrease a cost with the deadline assurance. Secondly, the resource profiling based placement phase locates a VM to a certain physical host in the multi-cloud using the profile on the property of clouds in order to comply with the budget while maximizing the service quality. We implement mobile cloud brokering system with the two-phases algorithm and demonstrate that our proposed system outperforms traditional cloud systems through several experimental results.

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KW - Mobile cloud brokering system

KW - Mobile cloud computing

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DO - 10.1007/s11036-015-0593-4

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VL - 20

SP - 328

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JO - Mobile Networks and Applications

JF - Mobile Networks and Applications

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ER -

Cost Adaptive VM Management for Scientific Workflow Application in Mobile Cloud

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Keywords

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