A Mathematical Model for Comparing Memory Storage of Three Interval-Based Parametric Temporal Database Models

Abstract

Interval-Based Parametric Temporal Database Model (IBPTDM) captures the historical changes of database object in single tuple. Such data model violates 1NF and it is difficult to be implemented on top of conventional Database Management Systems (DBMS). The reason behind that, IBPTDM cannot directly use relational storage structure or query evaluation technique that depends on atomic attribute values as well as it is unfixed attribute size. 1NF model with its features can be used to solve such challenge. Modeling time-varying data in 1NF model raise a question about memory storage efficiency and ease of use. A novel approach for representing temporal data in 1NF model and compare it with other main approaches in literature is the main goal of this research. To this end, a mathematical model for comparing a three different storage models is demonstrated to illustrate that the proposed model is more efficient than other approaches under certain conditions. The simulation results showed that the proposed model overcomes the needless redundancy of data, achieves saving in memory storage, and it is easy to be implemented in relational data model or to be adapted with a production systems that need to track temporal aspects of functioning database Systems.