位置相关信息服务中一种基于价值的数据预取方法

摘要

基于LDD的预取策略如DDP考虑了数据距离,但是没有考虑数据的访问概率和更新频率和数据大小,针对以上问题提出基于价值的数据预取(CDP)策略,一些重要的数据预取因素如访问概率、更新频率、数据项大小、数据距离和有效范围等都包含在价值函数里,根据价值函数值的大小来选择被预取的数据.通过实验对比,CDP比DDP策略更有效的提高缓存的命中率.%LDD-based prefetching strategies like DDP take the data distance into account, but do not take into account the access probability of data, updating data and size of frequency.For these issues, this paper proposes a value-based data prefetching (CDP) strategy, and some important data prefetching factors, such as access probability, update frequency, data item size, data distance and range of data are included in the value function.We can choose the prefetching data based on the size of function value.By comparing the experiment, CDP is more effective than DDP strategy to improve the cache hit rate.