The number of cloud services has dramatically increased over the past few years. Consequently, finding a service with the most suitable quality of service (QoS) criteria matching the user’s requirements is becoming a challenging task. Although various decision-making methods have been proposed to help users to find their required cloud services, some uncertainties such as dynamic QoS variations hamper the users from employing such methods. Additionally, the current approaches use either static or average QoS values for cloud service selection and do not consider dynamic QoS variations. In this paper, we overcome this drawback by developing a broker-based approach for cloud service selection. In this approach, we use recently monitored QoS values to find a timeslot weighted satisfaction score that represents how well a service satisfies the user’s QoS requirements. The timeslot weighted satisfaction score is then used in Best-Worst Method, which is a multi-criteria decision-making method, to rank the available cloud services. The proposed approach is validated using Amazon’s Elastic Compute Cloud (EC2) cloud services performance data. The results show that the proposed approach leads to the selection of more suitable cloud services and is also efficient in terms of performance compared to the existing analytic hierarchy process-based cloud service selection approaches.

中文翻译：

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使用最差方法和时隙加权满意度得分的动态QoS感知云服务选择

在过去的几年中，云服务的数量急剧增加。因此，找到具有最符合用户需求的最合适服务质量（QoS）标准的服务已成为一项具有挑战性的任务。尽管已经提出了各种决策方法来帮助用户找到他们所需的云服务，但是诸如动态QoS变化之类的一些不确定性阻碍了用户采用这种方法。另外，当前的方法将静态或平均QoS值用于云服务选择，并且不考虑动态QoS变化。在本文中，我们通过开发基于代理的云服务选择方法来克服此缺点。用这种方法 我们使用最近监视的QoS值来找到一个时隙加权满意度得分，该得分表示服务满足用户QoS要求的程度。然后，在多准则决策方法Best-Worst Method中使用时隙加权满意度分数对可用的云服务进行排名。该提议的方法已使用Amazon的Elastic Compute Cloud（EC2）云服务性能数据进行了验证。结果表明，与现有的基于层次结构的分析云服务选择方法相比，该方法可以选择更合适的云服务，并且在性能方面也非常有效。该提议的方法已使用Amazon的Elastic Compute Cloud（EC2）云服务性能数据进行了验证。结果表明，与现有的基于层次结构的分析云服务选择方法相比，该方法可以选择更合适的云服务，并且在性能方面也非常有效。该提议的方法已使用Amazon的Elastic Compute Cloud（EC2）云服务性能数据进行了验证。结果表明，与现有的基于层次结构的分析云服务选择方法相比，该方法可以选择更合适的云服务，并且在性能方面也非常有效。