On backwards windows

Continuing the series of posts about temporal windows:
Like the clock going backwards in this picture, one type of window is a window that is opened backwards.  The idea is that when event occurs, open a window backwards, to start either in some time offset, or by an occurrence of a specified event.   This is another type of window that is supported by some models, and emulated by using queries to databases that store past events in most models.   


An example is that an event processing system detects, using some pattern detection, that a person is a suspect in money laundering,  but substantiate the suspect is done by looking for another pattern on past event history.   This is known as "reinforcement" pattern use.  


The main difference between forward and backwards windows, is that in regular forward windows, events are being kept in the internal state only if they are required by some EPA which lives within this window, thus the events that should be kept in the system's state are well defined.   
In the backwards window case, since the window is not open when the event occur, then it should still be kept, thus we need to know of all possible backwards windows that might access this event in order to determine if an event should be kept,  or just keep all possible events (which in the most flexible case, since it allow unrestricted addition of backwards windows,  but may not be practical, as we may not know that an event even exists until some EPA that consumes it within a backwards window is defined.


This posting concludes the series of postings on temporal windows - for now.