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

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.