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Entropy-Based Service Selection with Uncertain QoS for Mobile Cloud Computing

机译:用于移动云计算的具有不确定QoS的基于熵的服务选择

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With the prevalence of mobile computing and its convergence with cloud computing, there is an increasing trend of composing existing cloud services for rapid development of cloud-based mobile applications. It is vital for developers to find services not only satisfying their functionality requirements, but also meeting the requirements on non-functional quality of services (QoS). These QoS requirements, such as throughput, delay, reliability and security, are critical for the success of cloud-based mobile applications. In this paper, a QoS-based service ranking and selection approach is proposed to help developers select the service that best satisfies developers' QoS requirements from a set of services having already satisfied developers' functionality requirements in mobile cloud computing. Compared with state-of-the-art service ranking and selection techniques, our approach has the following advantages: 1) it uses intervals instead of fixed values to represent QoS of services, which are more flexible and practical in mobile cloud computing, 2) it enables developers to specify their QoS requirements in a more simple way, and 3) it employs the hybrid weights that incorporate the Entropy-based weighting technique to overcome the weakness caused by subjective weights, which ignore the knowledge of different services' performance in different QoS aspects. Experiments validate the effectiveness of the proposed method.
机译:随着移动计算的盛行及其与云计算的融合,为基于云的移动应用程序的快速开发,组合现有的云服务的趋势正在日益增长。对于开发人员来说,找到不仅满足其功能要求而且还满足非功能服务质量(QoS)要求的服务至关重要。这些QoS要求,例如吞吐量,延迟,可靠性和安全性,对于基于云的移动应用程序的成功至关重要。本文提出了一种基于QoS的服务排名和选择方法,以帮助开发人员从已经满足移动云计算功能需求的一组服务中选择最能满足开发人员QoS要求的服务。与最新的服务排名和选择技术相比,我们的方法具有以下优势:1)它使用间隔而不是固定值来表示服务的QoS,这在移动云计算中更加灵活和实用; 2)它使开发人员能够以更简单的方式指定其QoS要求; 3)它采用了混合权重,该权重结合了基于熵的加权技术,从而克服了由主观权重引起的弱点,这些主观权重忽略了不同服务在不同情况下的性能知识QoS方面。实验验证了该方法的有效性。

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