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Framework for Ranking Service Providers of Federated Cloud Architecture using Fuzzy Sets

机译:使用模糊集对联合云体系结构的服务提供者进行排名的框架

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Federated Cloud Architecture is a heterogeneous and distributed model that provides infrastructures related to the cloud by aggregating different Infrastructure-as-a-Service (IaaS) providers. In this case, it is an exciting task to select the optimal service cloud provider for the customer and then deploy it. In this paper, a new provider discovery algorithm and fuzzy sets ranking model is proposed in the modified federated architecture and then the performance is evaluated. The proposed discovery method shortlists the provider based on the Quality of Service (QoS) indicators suggested by the Service Measurement Index (SMI) with the Service Level Agreement (SLA) that provides improved performance. In addition to that, the cost is also included that represents the fulfillment at the level of the end user. The ranking mechanism is based on a Fuzzy set approach, having three general phases, such as problem decomposition, judgment of priorities and an aggregation of these priorities. With some simple rules, the fuzzy set may be combined with the QoS indicators. The Weighted Tuned Queuing Scheduling (WTOS) Algorithm is proposed to resolve the issue of starvation in the existing architecture and manage the requests effectively. Experimental results show that the proposed architecture has a better successful selection rate, average response time and less overhead, compared to the existing architecture that had supported the Cloud environment.
机译:联合云架构是一种异构的分布式模型,通过聚合不同的基础架构即服务(IaaS)提供程序来提供与云相关的基础架构。在这种情况下,为客户选择最佳的服务云提供商然后进行部署是一项激动人心的任务。本文在改进的联邦体系结构中提出了一种新的提供商发现算法和模糊集排序模型,然后对其性能进行了评估。所提出的发现方法根据服务质量指数(SMI)和服务水平协议(SLA)建议的服务质量(QoS)指标建议提供商,从而提高性能。除此之外,还包括代表最终用户级别的实现成本。排名机制基于模糊集方法,具有三个一般阶段,例如问题分解,优先级判断和这些优先级的汇总。通过一些简单的规则,可以将模糊集与QoS指标组合在一起。为了解决现有架构中的饥饿问题并有效地管理请求,提出了加权调谐排队调度算法。实验结果表明,与支持云环境的现有架构相比,该架构具有更好的成功选择率,平均响应时间和更少的开销。

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