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Open AccessArticle

Cloud-Based Parameter-Driven Statistical Services and Resource Allocation in a Heterogeneous Platform on Enterprise Environment

1
Department of Computer Information and Science, Korea University, Sejong 30019, Korea
2
Department of Computer Science and Engineering, Seoul Women’s University, Seoul 01797, Korea
*
Author to whom correspondence should be addressed.
Academic Editors: Ka Lok Man, Yo-Sub Han and Hai-Ning Liang
Symmetry 2016, 8(10), 103; https://doi.org/10.3390/sym8100103
Received: 31 July 2016 / Revised: 14 September 2016 / Accepted: 20 September 2016 / Published: 29 September 2016
(This article belongs to the Special Issue Symmetry in Systems Design and Analysis)
A fundamental key for enterprise users is a cloud-based parameter-driven statistical service and it has become a substantial impact on companies worldwide. In this paper, we demonstrate the statistical analysis for some certain criteria that are related to data and applied to the cloud server for a comparison of results. In addition, we present a statistical analysis and cloud-based resource allocation method for a heterogeneous platform environment by performing a data and information analysis with consideration of the application workload and the server capacity, and subsequently propose a service prediction model using a polynomial regression model. In particular, our aim is to provide stable service in a given large-scale enterprise cloud computing environment. The virtual machines (VMs) for cloud-based services are assigned to each server with a special methodology to satisfy the uniform utilization distribution model. It is also implemented between users and the platform, which is a main idea of our cloud computing system. Based on the experimental results, we confirm that our prediction model can provide sufficient resources for statistical services to large-scale users while satisfying the uniform utilization distribution. View Full-Text
Keywords: cloud computing environments; data analysis; statistical analysis; data mining; heterogeneous platform; enterprise system cloud computing environments; data analysis; statistical analysis; data mining; heterogeneous platform; enterprise system
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MDPI and ACS Style

Lee, S.; Jeong, T. Cloud-Based Parameter-Driven Statistical Services and Resource Allocation in a Heterogeneous Platform on Enterprise Environment. Symmetry 2016, 8, 103. https://doi.org/10.3390/sym8100103

AMA Style

Lee S, Jeong T. Cloud-Based Parameter-Driven Statistical Services and Resource Allocation in a Heterogeneous Platform on Enterprise Environment. Symmetry. 2016; 8(10):103. https://doi.org/10.3390/sym8100103

Chicago/Turabian Style

Lee, Sungju; Jeong, Taikyeong. 2016. "Cloud-Based Parameter-Driven Statistical Services and Resource Allocation in a Heterogeneous Platform on Enterprise Environment" Symmetry 8, no. 10: 103. https://doi.org/10.3390/sym8100103

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