不确定数据库中减小可能世界的RPW-kBest查询

A RPW-kBest Query Based on Reduced Possible World in Uncertain Database

不确定数据普遍存在于大量应用之中,如在传感器网络、P2P系统、移动计算及RFID(Radio Frequency IDentifica-tion)等,研究者已经提出了多种针对不确定数据库的数据模型,其核心思想都源自于可能世界模型。针对可能世界模型能够演化出数量远大于不确定数据库规模的可能世界实例,文中提出一种减小可能世界的RPW-kBest算法,此算法利用概率和评定条件进行筛选,尽可能将不影响查询结果的数据抛弃,使之在最小的搜索空间内完成查询处理过程,以降低存储开销。实验结果表明,此算法能正确的得到查询结果并显著提高查询效率和降低内存使用。

Uncertain data arises from a few important applications. Such as wireless sensor networks,P2P systems, mobile computing and RFID technologh. Many data models have been developed, stemming from the core possible world model. For the possible world models contains a huge ntmther of the possible world instances which is far greater than the volume of the uncertain database, so a high-efficiency RPW-kBest Query be proposed, which reduces the possible world and a lower storage cost. The algorithm computes the bound of the probability and filter the data entries as much as possible , which have no chance to influence the query result and process RPW-kBest queries in a smallest search space. Experiments show that the algorithm can process the queries correctly and efficiently improved query efficiency and little memory usage.