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A framework of cloud service selection with criteria interactions

机译：具有标准交互的云服务选择框架

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摘要

Existing cloud service selection techniques assume that service evaluation criteria are independent. In reality, there are different types of interactions between criteria. These interactions influence the performance of a service selection system in different ways. In addition, a lack of measurement indices to validate the performance of service selection methods has hindered the development of decision making techniques in the service selection area. This paper addresses these critical issues of modeling the interactions between cloud service selection criteria, and designing indices to validate service selection methods. In this paper, we propose a Cloud Service Selection with Criteria Interactions framework (CSSCI) that applies a fuzzy measure and Choquet integral to measure and aggregate non-linear relations between criteria. We employ a non-linear constraint optimization model to estimate the Shapley importance and criteria interaction indices. In addition, we design a priority-based CSSCI (PCSSCI) to solve service selection problems in the situation where there is a lack of historical information to determine criteria relations and weights. Furthermore, we discuss an approximate solution for CSSCI to reduce its computing complexity. Finally, we design three indices to validate the cloud service selection methods. The experimental results preliminarily prove the technical advantage of the proposed models in contrast to several existing models. (C) 2018 Elsevier B.V. All rights reserved.
机译：现有的云服务选择技术假定服务评估标准是独立的。实际上，标准之间存在不同类型的交互。这些交互以不同的方式影响服务选择系统的性能。另外，缺乏用于验证服务选择方法性能的度量指标阻碍了服务选择领域决策技术的发展。本文解决了建模云服务选择标准之间的交互以及设计索引以验证服务选择方法的这些关键问题。在本文中，我们提出了一种具有标准交互作用的云服务选择框架（CSSCI），该框架应用模糊度量和Choquet积分来度量和聚合标准之间的非线性关系。我们采用非线性约束优化模型来估计Shapley重要性和标准交互作用指数。此外，我们设计了基于优先级的CSSCI（PCSSCI），以解决在缺乏确定标准关系和权重的历史信息的情况下的服务选择问题。此外，我们讨论了CSSCI的近似解决方案以降低其计算复杂性。最后，我们设计了三个指标来验证云服务选择方法。实验结果初步证明了与几种现有模型相比所提出模型的技术优势。 （C）2018 Elsevier B.V.保留所有权利。

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  • 来源
    《Future generation computer systems》 |2019年第5期|749-764|共16页
  • 作者

    Sun Le; Dong Hai; Hussain Omar Khadeer; Hussain Farookh Khadeer; Liu Alex X.;

  • 作者单位

    Nanjing Univ Informat Sci & Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Nanjing 210044, Jiangsu, Peoples R China|Michigan State Univ, Dept Comp Sci & Engn, E Lansing, MI 48824 USA;

    RMIT Univ, Sch Sci, Melbourne, Vic, Australia;

    UNSW, Australian Def Force Acad, Sch Business, Canberra, ACT, Australia;

    Univ Technol Sydney, Sch Software, Ctr Artificial Intelligence, Sydney, NSW, Australia;

    Nanjing Univ Informat Sci & Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Nanjing 210044, Jiangsu, Peoples R China|Michigan State Univ, Dept Comp Sci & Engn, E Lansing, MI 48824 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Cloud service selection; Criteria interactions; Fuzzy measure; Measurement indices of MCDMs;

    机译：云服务选择;准则交互;模糊度量;MCDM度量指标;

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