双时态周期数据模型的研究

在经典的时态数据模型HMAP的基础上，通过增加事务时间参数delay的方式，提出了一种支持多时间粒度，可以有效处理具有周期特性数据的双时态数据模型PMB，该数据模型可以有效地解决HMAP模型存储中记录条目繁多和时间交叉的问题，从而节约存储空间，提高数据的查询速度。 理论分析和实验结果表明PMB数据模型可以把需要存储为n条记录的数据简化为有限的几条，而且当n值很大，甚至无穷的时候，这种存储方式具有明显的优势。

Research on Bi-temporal Periodic Data Model

This paper proposes a new multi-granularities bi-temporal data model PMB, based on the classical HMAP model, by introducing the definition of transaction period parameter delay, to process the periodic data. The proposed model can efficiently deal with the problems of enormous record items and intersectant time points existing in the HMAP model, which will save the store space and improve the speed of searching for data. Theoretical analysis and experimental results show that the PMB model can make n items of the list cut short to a few items. When the value of n is very enormous, the advantage of this model is very prominent.