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An Efficient Technique for Trust Based Cloud Providers Ranking in Federated Cloud

机译:基于信任的云提供商在联邦云中排名的高效技术

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摘要

Cloud computing is a convenience worked out model that permits consumers to flexibly attain virtualized computing possessions. In this study, a representation for trust management based upon Fuzzy Logic has been enhanced, which aid clients can formulate a knowledgeable selection to picking the suitable CSP. The majority characteristic that implement conviction in the cloud are high-quality point of protection and accessibility. Additionally, an extremely consistent cloud function is indicated to be reliable. Therefore, cloud conviction should be an inclusive catalog and categorize more than a few conviction feature of a function, such as protection, accessibility and consistency. In the projected method, conviction scheme depend on the optimization procedure is projected to make a decision on the standard cloud function contributor for the consumers. The grade of the cloud contributor is projected by the optimization algorithm. The optimization algorithm is exploited in the projected technique as Hybrid Artificial Bee Colony Optimization (HABC), where Cuckoo Search Algorithm is enhanced for optimization of fuzzy logic methods and innovative broker learning algorithm. The result is allocated for the service contributors depend on the fitness value. The service contributors are categorized by conviction.
机译:云计算是一种便利化的模型,允许消费者灵活地获得虚拟计算财产。在这项研究中,基于模糊逻辑的基于模糊逻辑的信任管理的表示,援助客户可以制定知识渊博的选择以挑选合适的CSP。在云中实施定罪的多数特征是高质量的保护点和可访问性。另外,表示极其一致的云功能是可靠的。因此,云定罪应该是包含的包含目录,并分类为函数的一些定罪功能,例如保护,可访问性和一致性。在预计的方法中,定罪方案取决于优化程序,预计会对消费者的标准云功能贡献者作出决定。通过优化算法预测云贡献者的等级。优化算法在预计技术中利用作为混合人工蜂殖民地优化(HABC),其中Cuckoo搜索算法得到了模糊逻辑方法的优化和创新经纪人学习算法。为服务贡献者分配了结果,取决于健身值。服务贡献者被定罪分类。

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