Data reduction in real time database using critical and pivot points

Abstract EN

Data reduction is the important thing in the real time database but the information in this data must not be changed.

There are very huge data in the real time system and all these data must not be stored because the restriction in storage media.

The general method which is widely used is comparing the recent data with the previous data, if there is change in the value by a factor or large from this factor, the recent value is stored otherwise the current value is not stored.

Periodically (daily, weekly or monthly), the data is deleted if there is no need for to it.

Here another suggestion is added to this method according which pivot and critical points and specific factor specify the points which can be deleted.

This is done according to the increasing and decreasing in the values of data, and then the middle points can be deleted.

This deleted data can be retrieved mathematically approximately (near original data).

This method has been tested on real data and it’s successful.