Research On A TDBMS Extension Based On Temporal Granularity Conformity Module

Temporal database should support user to define time. But the user may define time granularities in their wills. Temporal database should support the user to manipulate data in any time unit. But in the several implementations of temporal database, it is the user application, rather than the TDBMS that implements the time management. This thesis discusses the way in which the temporal database manages these time granularities, converts between different time granularity representations of information, and makes the conversion transparent to users.This thesis extends the TDBMS of TimeDB to promote a Temporal Granularity Conformity Module (TGCM). TGCM consists of Algorithm Executing Component (AEC) and Intelligent Learning Component (ILC).AEC communicates with user interface and executes Conformation Algorithm to convert data into different time granularity representation.ILC can learn the time unit users defined, the relation IN between time units, the conversion functions, and the addtionablity of data . ILC deploys Meta Database and Metadata Object Model to manage those functions.The TGCM works as an extended module in the TDBMS to support the characteristics of multiple time granularities. If the time granularity of result set is different from the time unit the data stored in the database, AEC and ILC could cooperate to make the conversion totally transparent to user. By this way, managing time granularities by TDBMS is completely achieved.