Research On Mobile Cloud Scheduling Based On Mutil-level User Attributes

With the development of Internet technology, the trend of technology convergence is becoming more and more obvious. The emergence of cloud computing has brought an effective solution to the problem of big data, and the trend of intelligent equipment and mobile technology allows people to use the Internet anytime, anywhere. Mobile Cloud Computing(MCC) is a new development of technology convergence in the current environment. It is based on the development of cloud computing and mobile Internet, it combines the advantages of both, but also brings new problems.The main topic of this thesis is mainly the two basic issues in mobile cloud scheduling: 1) how to reduce the data size and accelerate cloud scheduling speed; 2) according to the demand of users, how to bring more personalized services for them in the scheduling.In order to solve the above problems, this paper studies the mobile cloud scheduling algorithm, and proposes a mobile cloud scheduling system based on multi-layer user attributes. Fuzzy clustering can classify things, so that the problem can be solved in a more precise range.Therefore, this paper proposes a related improved algorithm (IGAFCM)based on the fuzzy clustering algorithm, to solve the data problem in Mobile Cloud Scheduling. At the same time, this paper also uses the collaborative filtering algorithm in recommender systems (FCMCF),developed a scoring model based on multi-level user attributes, so that the system can offer more personalized service for users during scheduling.Finally, we use the simulation tools such as Matlab and CloudSim to verify the algorithms and the scheduling system.