中文摘要：

一个动态数据库格子( DBG )和一个分布式的数据库系统的数据集成之间的差别被分析，并且三种数据集成策略在 DBG 的背景上被给基于 p2p ( P2P )框架，包括集中的数据集成( CDI )策略，分布式的数据集成(滴滴滴策略和 基于thefilter 的数据集成(光纤分布式数据接口)策略。CDI 把所有数据库称为格子服务(DGS ) 在作为壁炉节点， DDI 驱散 DGSsto 多重节点，当光纤分布式数据接口基于过滤安排数据集成节点时，关键词从 DGS 回来了。这三集成策略的表演与相比并且由模拟实验分析。光纤分布式数据接口为与数据冗余性增加过滤关键词是更明显的。通过大量数据交通的减小，它有效地弄短这项任务的执行时间并且改进它的效率。

英文摘要：

The differences between the data integration of a dynamic database grid （DBG） and that of a distributed database system are analyzed, and three kinds of data integration strategies are given on the background of DBG based on Peer to Peer （P2P） framework, including the centralized data integration （CDI） strategy, the distributed data integration （DDI） strategy and the filter-based data integration （FDDI） strategy. CDI calls all the database grid services （DGSs） at a single node, DDI disperses the DGSs to multiple nodes, while FDDI schedules the data integration nodes based on filtering the keywords returned from DGSs. The performance of these three integration strategies are compared with and analyzed by simulation experiments. FDDI is more evident for filtering the keywords with data redundancy increasing. Through the reduction of large amount of data transportation, it effectively shortens the executing time for the task and improves its efficiency.