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

机译:数据预取策略在移动学习环境中支持实时交易处理的研究

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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 construcingt the selected function of expected data it not only considers the time-liness 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.
机译:在移动环境中,当下载和打开学习资源时,它需要大的数据通信带宽和强大的数据处理能力。由于移动环境的内在局限性,数据访问可能存在长时间延迟。数据预取方法是此问题的方法。在本文中,提出了一种改进的数据预取策略。基于存在的研究,当解释预期数据的所选函数时,它不仅考虑数据对象事务的截止日期,而且考虑对象数据的事件的可变性,活动和优先权因素。因此,它可以具有更高的实验结果表明,数据预取策略可以降低移动实时事件的截止日期比,并且可以有效地支持移动移动学习资源提取。

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