Selecting appropriate cloud solution for managing big data projects using hybrid AHP-entropy based assessment

Nitin Sachdeva, P. K. Kapur, Gurinder Singh
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引用次数: 7

Abstract

Today technology that learns from data to forecast future behavior of individuals, organizations, government and country as a whole, is playing a crucial role in the advancement of human race. In fact, the strategic advantage most of the companies today strive for are use of new available technologies like cloud computing and big data. However, today's dynamic business environment poses severe challenges in front of companies as to how to make use of the power of big data with the technical flexibility that cloud computing provides? Therefore, evaluating, ranking and selecting the most appropriate cloud solution to manage big data project is a complex concern which requires multi criteria decision environment. In this paper we propose a hybrid entropy method combined with Analytical Hierarchical Process (AHP) to select appropriate cloud solution to manage big data projects in group decision making environment. In order to collate individual opinions of decision makers for rating the importance of various criteria and alternatives, we employed usability analysis using the proposed hybrid AHP-Entropy method.
选择合适的云解决方案,使用基于混合层次分析法熵的评估来管理大数据项目
今天,从数据中学习预测个人、组织、政府和整个国家未来行为的技术,在人类的进步中发挥着至关重要的作用。事实上,今天大多数公司努力争取的战略优势是使用新的可用技术,如云计算和大数据。然而,当今动态的商业环境对企业提出了严峻的挑战,如何利用云计算提供的技术灵活性来利用大数据的力量?因此,评估、排序和选择最合适的云解决方案来管理大数据项目是一个复杂的问题,需要多标准的决策环境。本文提出了一种结合层次分析法(AHP)的混合熵方法来选择合适的云解决方案来管理群体决策环境下的大数据项目。为了整理决策者对评价各种标准和备选方案的重要性的个人意见,我们使用提出的混合ahp -熵方法进行可用性分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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