In cloud computing,the number of replicas and deployment strategy have extensive impacts on user's requirement and storage efficiency.Therefore,in this paper,a new definition of file access popularity according to...In cloud computing,the number of replicas and deployment strategy have extensive impacts on user's requirement and storage efficiency.Therefore,in this paper,a new definition of file access popularity according to users' preferences,and its prediction algorithm are provided to predict file access trend with historical data.Files are sorted by priority depending on their popularity.A mathematical model between file access popularity and the number of replicas is built so that the reliability is increased efficiently.Most importantly,we present an optimal strategy of dynamic replicas deployment based on the file access popularity strategy with the overall concern of nodes' performance and load condition.By this strategy,files with high priority will be deployed on nodes with better performance therefore higher quality of service is guaranteed.The strategy is realized in the Hadoop platform.Performance is compared with that of default strategy in Hadoop and CDRM strategy.The result shows that the proposed strategy can not only maintain the system load balance,but also supply better service performance,which is consistent with the theoretical analysis.展开更多
With the development of mobile technologies,mobile learning has become a trend and a necessary means in the e-learning environment.E-learners' autonomous learning processes can also be facilitated through the adop...With the development of mobile technologies,mobile learning has become a trend and a necessary means in the e-learning environment.E-learners' autonomous learning processes can also be facilitated through the adoption of various mobile learning tools.Mobile learning tools can be classified into different types according to their different features and functions.Mobile learning devices,mobile learning software,mobile learning resources,and mobile learning services are the four types of learning tools suggested in the paper.Different mobile learning tools are proven to be able to fulfill different needs of autonomous learning.展开更多
基金Supported by the National Natural Science Foundation of China(No.61170209,61272508,61202432,61370132,61370092)
文摘In cloud computing,the number of replicas and deployment strategy have extensive impacts on user's requirement and storage efficiency.Therefore,in this paper,a new definition of file access popularity according to users' preferences,and its prediction algorithm are provided to predict file access trend with historical data.Files are sorted by priority depending on their popularity.A mathematical model between file access popularity and the number of replicas is built so that the reliability is increased efficiently.Most importantly,we present an optimal strategy of dynamic replicas deployment based on the file access popularity strategy with the overall concern of nodes' performance and load condition.By this strategy,files with high priority will be deployed on nodes with better performance therefore higher quality of service is guaranteed.The strategy is realized in the Hadoop platform.Performance is compared with that of default strategy in Hadoop and CDRM strategy.The result shows that the proposed strategy can not only maintain the system load balance,but also supply better service performance,which is consistent with the theoretical analysis.
基金Beijing Higher Education Young Elite Teacher Project,China(No.YETP0471)
文摘With the development of mobile technologies,mobile learning has become a trend and a necessary means in the e-learning environment.E-learners' autonomous learning processes can also be facilitated through the adoption of various mobile learning tools.Mobile learning tools can be classified into different types according to their different features and functions.Mobile learning devices,mobile learning software,mobile learning resources,and mobile learning services are the four types of learning tools suggested in the paper.Different mobile learning tools are proven to be able to fulfill different needs of autonomous learning.
