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Proposal for an optimal job allocation method for data-intensive applications based on multiple costs balancing in a hybrid cloud environment

Authors:

Yumiko Kasae,

Masato OguchiAuthors Info & Claims

ICUIMC '13: Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication

Article No.: 5, Pages 1 - 8

https://doi.org/10.1145/2448556.2448561

Published: 17 January 2013 Publication History

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Abstract

Due to the explosive increase in the amount of information in computer systems, we need a system that can process large amounts of data efficiently. Cloud computing system is an effective means to achieve this capacity and has spread throughout the world. In our research, we focus on hybrid cloud environments, and we propose a method for efficiently processing large amounts of data while responding flexibly to needs related to performance and costs. We have developed this method as middleware.

For data-intensive jobs using this system, we have created a benchmark that can determine the saturation of the system resources deterministically. Using this benchmark, we can determine the parameters in this middleware. This middleware can provide Pareto optimal cost load balancing based on the needs of the user. The results of the evaluation indicate the success of the system.

We then compare the processing time when these jobs are processed sequentially and the processing time using this measurement.

References

[1]

Eucalyptus: http://www.eucalyptus.com/

Google Scholar

[2]

Amazon EC2: http://aws.amazon.com/jp/ec2/

Google Scholar

[3]

SHW3A: http://www.system-artware.co.jp/shw3a.html

Google Scholar

[4]

Gueyoung Jung, Kaustubh R. Joshi, Matti A. Hiltunen, Richard D. Schlichting and Calton Pu, "Generating Adaptation policies for Multi-Tier Applications in Consolidated Server Environments", In Proc. 5th IEEE International Conference on Autonomic Computing (ICAC2008), p23--32, June, 2008.

Digital Library

Google Scholar

[5]

Evangelia Kalyvianaki, Themistoklis Charalambous and Steven Hand, "Self-Adaptive and Self-Configured CPU Resource Provisioning for Virtualized Servers Using Kalman Filters", In Proc. 6th International Conference on Autonomic Computing and Communications (ICAC2009)", June, 2009

Digital Library

Google Scholar

[6]

Shiori Toyoshima, Saneyasu Yamaguchi, Masato Oguchi, "Middleware for Load Distribution among Cloud Computing Resource and Local Cluster used in the Execution of Data-Intensive Application", Journal of the Database Society of Japan, Vol. 10, No. 1, pp. 31--36, June, 2011

Google Scholar

[7]

Kazuki Mochizuki and Shin-ichi Kuribayashi, "Evaluation of Optimal Resource Allocation Method for Cloud Computing Environments with Limited Electric Power Capacity," In Proc. 2011 14th International Conference on Network-Based Information Systems, pp. 1--5, 2011

Digital Library

Google Scholar

[8]

Che-Yuan Tu, Wen-Chieh Kuo, Wei-Hua Teng, Yao-Tsung Wang, Steven Shiau, "A Power-Aware Cloud Architecture with Smart Metering", In Proc. Parallel Processing Workshops (ICPPW), 2010 39th International Conference, pp. 497--503, Sep, 2010

Digital Library

Google Scholar

[9]

Cathryn Peoples, Gerard Parr and Sally McClean, "Energy-aware data centre management", In Proc. Communications (NCC), 2011 National Conference, pp. 1--5, Jan, 2011

Crossref

Google Scholar

[10]

By Jayant Baliga, Robert W. A. Ayre, Kerry Hinton, and Rodney S. Tucker, "Green Cloud Computing: Balancing Energy In Processing, Storage, and Transport", Proceedings of the IEEE, pp. 149--167, Jan, 2011

Crossref

Google Scholar

[11]

Gueyoung Jung, Matti A. Hiltunen, Kaustubh R. Joshi, Richard D. Schlichting, Calton Pu "Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures", In Proc. Distributed Computing Systems (ICDCS), 2010 IEEE 30th International Conference, pp. 62--73, June, 2010

Digital Library

Google Scholar

[12]

Luna Mingyi Zhang, Keqin Li, Yan-Qing Zhang, "Green Task Scheduling Algorithms with Speeds Optimization on Heterogeneous Cloud Servers", In Proc. Green Computing and Communications (GreenCom), 2010 IEEE/ACM Int'l Conference on and Int'l Conference on Cyber, Physical and Social Computing (CPSCom), pp. 76--80, Dec, 2010

Digital Library

Google Scholar

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Azumah KSorensen LTadayoni R(2018)Hybrid Cloud Service Selection Strategies: A Qualitative Meta-Analysis2018 IEEE 7th International Conference on Adaptive Science & Technology (ICAST)10.1109/ICASTECH.2018.8506887(1-8)Online publication date: Aug-2018
https://doi.org/10.1109/ICASTECH.2018.8506887
Li C(2015)Hybrid cloud service selection strategyComputer Applications in Engineering Education10.1002/cae.2163423:5(645-657)Online publication date: 1-Sep-2015
https://dl.acm.org/doi/10.1002/cae.21634
Maneewongvatana SManeewongvatana S(2013)Hybrid cloud load prediction model for LMS applications based on class activity patterns2013 International Joint Conference on Awareness Science and Technology & Ubi-Media Computing (iCAST 2013 & UMEDIA 2013)10.1109/ICAwST.2013.6765450(292-298)Online publication date: Nov-2013
https://doi.org/10.1109/ICAwST.2013.6765450

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Proposal for an optimal job allocation method for data-intensive applications based on multiple costs balancing in a hybrid cloud environment

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ICUIMC '13: Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication

January 2013

772 pages

ISBN:9781450319584

DOI:10.1145/2448556

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 17 January 2013

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Ministry of Education, Culture, Sports, Science, and Technology

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ICUIMC '13

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SIGAPP
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ICUIMC '13: The 7th International Conference on Ubiquitous Information Management and Communication

January 17 - 19, 2013

Kota Kinabalu, Malaysia

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Azumah KSorensen LTadayoni R(2018)Hybrid Cloud Service Selection Strategies: A Qualitative Meta-Analysis2018 IEEE 7th International Conference on Adaptive Science & Technology (ICAST)10.1109/ICASTECH.2018.8506887(1-8)Online publication date: Aug-2018
https://doi.org/10.1109/ICASTECH.2018.8506887
Li C(2015)Hybrid cloud service selection strategyComputer Applications in Engineering Education10.1002/cae.2163423:5(645-657)Online publication date: 1-Sep-2015
https://dl.acm.org/doi/10.1002/cae.21634
Maneewongvatana SManeewongvatana S(2013)Hybrid cloud load prediction model for LMS applications based on class activity patterns2013 International Joint Conference on Awareness Science and Technology & Ubi-Media Computing (iCAST 2013 & UMEDIA 2013)10.1109/ICAwST.2013.6765450(292-298)Online publication date: Nov-2013
https://doi.org/10.1109/ICAwST.2013.6765450

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Cost-Effective Service Provisioning for Hybrid Cloud Applications

Power & Load Aware Resource Allocation Policy for Hybrid Cloud

Resource Allocation with Efficient Load Balancing in Cloud Environment

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