A cost-effective intelligent configuration model in cloud computing

Wei Tek Tsai; Guanqiu Qi; Yinong Chen

doi:10.1109/ICDCSW.2012.46

A cost-effective intelligent configuration model in cloud computing

Wei Tek Tsai^*
, Guanqiu Qi
, Yinong Chen

^*Corresponding author for this work

Arizona State University
Tsinghua University

Research output: Contribution to conference › Paper › peer-review

29 Scopus citations

Abstract

Cloud computing environments provide a resource pool for customers for their processing, storage and networking needs. It is necessary for customers to choose desirable configuration from vast resources available in the cloud. This paper proposes a heuristic model to choose a cloud configuration for efficient use. Trend analysis in data mining is used to predict the future trend and assist provisioning. The model is experimented with Intel power 32 core machine and in Azure cloud. Both environments demonstrated that the proposed model provided effective solutions.

Original language	English
Pages	400-408
Number of pages	9
DOIs	https://doi.org/10.1109/ICDCSW.2012.46
State	Published - 2012
Externally published	Yes
Event	32nd IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2012 - Macau, China Duration: 18 Jun 2012 → 21 Jun 2012

Conference

Conference	32nd IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2012
Country/Territory	China
City	Macau
Period	18/06/12 → 21/06/12

Keywords

cloud
configuration

Access to Document

10.1109/ICDCSW.2012.46

Cite this

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abstract = "Cloud computing environments provide a resource pool for customers for their processing, storage and networking needs. It is necessary for customers to choose desirable configuration from vast resources available in the cloud. This paper proposes a heuristic model to choose a cloud configuration for efficient use. Trend analysis in data mining is used to predict the future trend and assist provisioning. The model is experimented with Intel power 32 core machine and in Azure cloud. Both environments demonstrated that the proposed model provided effective solutions.",

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AB - Cloud computing environments provide a resource pool for customers for their processing, storage and networking needs. It is necessary for customers to choose desirable configuration from vast resources available in the cloud. This paper proposes a heuristic model to choose a cloud configuration for efficient use. Trend analysis in data mining is used to predict the future trend and assist provisioning. The model is experimented with Intel power 32 core machine and in Azure cloud. Both environments demonstrated that the proposed model provided effective solutions.

KW - cloud

KW - configuration

UR - https://www.scopus.com/pages/publications/84866389467

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A cost-effective intelligent configuration model in cloud computing

Abstract

Conference

Keywords

Access to Document

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