Research on Data Prefetching Strategy to Support Real-time Transactions Processing in Mobile Learning Environments

Youfu Du, Ming Zhao

Genetic and Evolutionary Computing(2010)

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Abstract
In mobile environment, when downloading and opening learning resources it would need the large data communications bandwidth and strong data processing ability. Due to the intrinsic limitations of a mobile environment, there can be long time latency for a data access. Data prefetching is an approach to this problem. in this paper, a improved data prefetching strategy was proposed. based on existed research, when construcing the selected function of expected data it not only considers the time-lines for deadlines of data objects transactions but also consider the changeability, activities and priority factors of events of object datas. Therefore it could have more efficient Experiments result shows that the data prefetching strategies can reduce the deadline ratio of the mobile real-time events, and could support mobile mobile learning resource extraction effectively.
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Key words
data access,mobile data,data prfetech,large data communications bandwidth,data prefetching,real-time transactions processing,mobile mobile learning resource,mobile learning environments,learning (artificial intelligence),mobile e-learning,storage management,information retrieval,mobile learning,transaction processing,object data,data prefetching strategy,timeliness,data objects transaction,expected data,support real-time transactions,deadlines,mobile environment,improved data,mobile computing,resource extraction,strong data,open learning,learning artificial intelligence,real time systems,real time,time frequency analysis,data processing,servers,corrosion,databases,mobile communication
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