Mobile cloud computing (MCC) has attracted extensive attention in recent years. With the prevalence of MCC, how to select\ntrustworthy and high quality mobile cloud services becomes one of the most urgent problems. Therefore, this paper focuses on\nthe trustworthy service selection and recommendation in mobile cloud computing environments. We propose a novel service\nselection and recommendation model (SSRM), where user similarity is calculated based on user context information and interest.\nIn addition, the relational degree among services is calculated based on PropFlowalgorithmandwe utilize it to improve the accuracy\nof ranking results. SSRM supports a personalized and trusted selection of cloud services through taking into account mobile user�s\ntrust expectation. Simulation experiments are conducted on ns3 simulator to study the prediction performance of SSRM compared\nwith other two traditional approaches. The experimental results show the effectiveness of SSRM.
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