用户约束相对重要性对物云资源发现的影响:一个案例研究

L. H. Nunes, J. C. Estrella, A. Delbem, Charith Perera, S. Reiff-Marganiec
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引用次数: 5

摘要

在过去几年中,与服务和应用程序的数量相比,连接到互联网的智能对象的数量呈指数级增长。云计算与物联网的融合,被称为物云,在管理被连接的事物及其数据和服务方面发挥着关键作用。物联网面临的主要挑战之一是智能对象的资源发现及其在不同环境中的重用。现有的工作大多使用某种多准则决策分析算法来执行资源发现,但没有评估用户约束对最终解决方案的影响。在本文中,我们分析了SAW、TOPSIS和VIKOR多目标决策分析算法的行为以及用户约束对它们的影响。我们使用帕累托最优概念评估了提出的解决方案的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Effects of Relative Importance of User Constraints in Cloud of Things Resource Discovery: A Case Study
Over the last few years, the number of smart objects connected to the Internet has grown exponentially in comparison to the number of services and applications. The integration between Cloud Computing and Internet of Things, named as Cloud of Things, plays a key role in managing the connected things, their data and services. One of the main challenges in Cloud of Things is the resource discovery of the smart objects and their reuse in different contexts. Most of the existent work uses some kind of multi-criteria decision analysis algorithm to perform the resource discovery, but do not evaluate the impact that the user constraints has in the final solution. In this paper, we analyse the behaviour of the SAW, TOPSIS and VIKOR multi-objective decision analyses algorithms and the impact of user constraints on them. We evaluated the quality of the proposed solutions using the Pareto-optimality concept.
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