Qoe Evaluation And Optimization Of Mobile Cloud Computing

In recent years, cloud computing has become a global field of information, especially in the frontier areas such as communication, computer, software and network. After several years of development, cloud computing has gone through the fuzzy stage, and becomes more focused and pragmatic, which is expected to start the stage of rapid development. Some innovative Internet companies use cloud platforms for low-cost and fast-response. Cloud computing reduces system deployment costs and operating expenses greatly, speeds up business online, which formes a huge industry scale, the enterprise value and social impact gradually.At the same time, users are more inclined to use the personalized mobile terminals such as smart phone, tablet PC and iTV etc.Through Internet and cloud computing, communications can occur between man and man, man and things, things and things. With the penetration of smart terminals, and the coming of3G and even4G era, the combination of cloud computing and mobile Internet will generate more business opportunities. Researching on the quality of user experience impact factors of mobile cloud computing, and optimizing mobile cloud computing user experience, which is conducive to the provider of mobile cloud computing business management and marketing.The study enhances steady and rapid development of mobile cloud computing business in China, and it has important theoretical and practical significance.This study includes five sections:Firstly we introduce business development and research background of mobile cloud computing, define the scope of research, and proposes the scientific problems.Secondly, we review the literature about cloud computing, QoE(quality of user experience),and optimization.Thirdly,we build the influence factors model of individual user QoE evaluation about mobile cloud computing, develop scale, collect data,and do empirical analysis. Fourthly, we build the model of business users QoE evaluation about mobile cloud computing, develop scale, collect data,and do empirical analysis.Finally, using the conclusion of the third and fourth part as input, we build individual user/business users QoE optimization model of mobile cloud computing respectively,and select actual examples to verify the analysis.This study applied the research methodology proposed by Wallance. Firstly, after expounding mobile cloud computing development status at home and abroad, we indicate the research significance and object, and describe the research programs and innovation. Then, based on the existing QoE theory, profiling and defining the relevant concepts and put forward the relationship between the reaction concept assumptions.we establish contact between mobile cloud computing individual user QoE evaluation and concepts such as performance expectancy, effort expectancy, social influence, enabling conditions, perceived value, perceived benefits, perceived cost, perceived risk. we establish contact between mobile cloud computing business users QoE evaluation and concepts such as functional experience, technology experience,process experience, human experience, result experience.After collecting data from the social survey, we use SPSS and AMOS to analyze data and validate assumptions.Finally, we build the QoE optimization model of mobile cloud computing, and Validate of the model by the actual data, in order to verify the correctness of the theory and triggered future research problems.After the theoretical and empirical analysis, we draw the following conclusions:(i) The conclusions of the influence factors model of individual user QoE evaluation about mobile cloud computing.In this study, each variable Kroner Bach alpha coefficient is above0.7, the overall reliability is0.886, the CITC values of most factor measurement projects are greater than0.3. The overall KMO test coefficient of the sample data is0.881, and the sample distribution spherical Bartlett test statistical significance is0.000. By factor analysis of the independent variables, the independent variables are automatically classified into seven factors, and the contribution rate is61.884%,which means strong interpretation strength. Due to the variable factor analysis, seven problems of dependent variables are classified into two factors, and the contribution rate is91.752%.The impacts for QoE evaluation of performance expectancy, effort expectancy, social impact, enabling conditions, perceived value are significantly (P<0.001) and positive. The impacts for perceived value of perceived benefits, perceived cost, perceived risk are significantly (P <0.001),and the impacts for perceived value of perceived cost, perceived risk are negative.Come to the conclusion, the positive core impact factors are "performance expectations"(path value R=0.44) and "social impact"(path value R=0.33); the negative core impact factors are "perceived cost"(path value R=-0.70)" and "perceived risk"(path to value R=-0.30).(ii) The conclusions of the model of business users QoE evaluation about mobile cloud computing.In this study, we set index weights by survey questionnaire which17experts filled in.According to the results of the65questionnaire,we use of fuzzy comprehensive evaluation method to make a comprehensive evaluation of mobile cloud computing individual user QoE. As can be seen from the results of the evaluation, the evaluation of mobile cloud computing individual user QoE is"quite satisfactory", and the degree of satisfaction is high (92%).But there still exist some short board of individual user QoE evaluation,such as" process of experience"(no satisfaction is15%)and "result experience"(no satisfaction is12%).They are embodied in"the security of work"," the security of user information"," human resources cost savings"and" work performance improvement".(iii) The conclusions of the individual user QoE optimization model of mobile cloud computing. In this study, we design the objective functions from "performance expectations","social impact","perceived cost" and "perceived risk".We select Youdao cloud notes as the example,concluded that when the Youdao company make invest decision to Youdao cloud notes,it should use18.8%of the funds for publicity,so as to enhance the individual user’s social impact goals.It should use52.6%of the funds for technological innovation of data processing capabilities,so as to enhance the user’s performance expectations,and reduce the cost of user perception. It should use28.6%of the funds for technological innovation of ecurity capabilities,so as to reduce perceived risk.According to the multi-objective optimization model,we can improve the individual user QoE by changing the funds invested proportion of provider,so as to balance the interests of providers and users,then achieve a win-win.(iv) The conclusions of the business users QoE optimization model of mobile cloud computing.In this study, we design the objective functions from"the security of information"," human resources cost savings"and" work performance improvement".We select IBM TAP (Technology Adoption Program) project as example,concluded that when IBM company make invest decision to TAP project,it should use42.5%of the funds for the enhancement of information security technology. It should use38.2%of the funds for optimization of the processing power to enhance job performance. It should use19.3%of the funds for hardware and software to save human capital investment. According to the multi-objective optimization model,we can improve the business users QoE by changing the funds invested proportion of provider,so as to balance the interests of providers and users,then achieve a win-win.