Literature DB >> 25170937

A service brokering and recommendation mechanism for better selecting cloud services.

Zhipeng Gui1, Chaowei Yang2, Jizhe Xia2, Qunying Huang2, Kai Liu2, Zhenlong Li2, Manzhu Yu2, Min Sun2, Nanyin Zhou2, Baoxuan Jin2.   

Abstract

Cloud computing is becoming the new generation computing infrastructure, and many cloud vendors provide different types of cloud services. How to choose the best cloud services for specific applications is very challenging. Addressing this challenge requires balancing multiple factors, such as business demands, technologies, policies and preferences in addition to the computing requirements. This paper recommends a mechanism for selecting the best public cloud service at the levels of Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). A systematic framework and associated workflow include cloud service filtration, solution generation, evaluation, and selection of public cloud services. Specifically, we propose the following: a hierarchical information model for integrating heterogeneous cloud information from different providers and a corresponding cloud information collecting mechanism; a cloud service classification model for categorizing and filtering cloud services and an application requirement schema for providing rules for creating application-specific configuration solutions; and a preference-aware solution evaluation mode for evaluating and recommending solutions according to the preferences of application providers. To test the proposed framework and methodologies, a cloud service advisory tool prototype was developed after which relevant experiments were conducted. The results show that the proposed system collects/updates/records the cloud information from multiple mainstream public cloud services in real-time, generates feasible cloud configuration solutions according to user specifications and acceptable cost predication, assesses solutions from multiple aspects (e.g., computing capability, potential cost and Service Level Agreement, SLA) and offers rational recommendations based on user preferences and practical cloud provisioning; and visually presents and compares solutions through an interactive web Graphical User Interface (GUI).

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Year:  2014        PMID: 25170937      PMCID: PMC4149509          DOI: 10.1371/journal.pone.0105297

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  1 in total

1.  A Geospatial Information Grid Framework for Geological Survey.

Authors:  Liang Wu; Lei Xue; Chaoling Li; Xia Lv; Zhanlong Chen; Mingqiang Guo; Zhong Xie
Journal:  PLoS One       Date:  2015-12-28       Impact factor: 3.240

  1 in total

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