next up previous
Next: Optimum Choice of Verification Up: Characteristics of the Predictive Previous: Characteristics of the Predictive

Tolerance and Accumulated Simulation Error

In order to consider the impact that out-of-tolerance rollback will have on the predictive system, consider how simulation error occurs. A predictive management system LP may deviate from the real object because either the LP does not accurately represent the actual entity or because events outside the scope of the predictive network management system may effect the entities being managed. Ignore events outside the scope of the simulation for now and consider error form inaccurate simulation modeling only.

Because of this possibility for prediction error, a method of determining the amount of error in a predicted result needs to be developed. A function of total accumulated error in a predicted result, tex2html_wrap_inline781 , is described by Equations 1 and 2. tex2html_wrap_inline783 is the error introduced by the virtual message injected into the predictive system by the driving process. The error introduced by the output message produced by the computation of each LP is represented by the computation error function, tex2html_wrap_inline785 . The actual time taken by the tex2html_wrap_inline787 LP to calculate and output the next virtual message is tex2html_wrap_inline789 . Note that the LP topology may not necessarily be a feed-forward network as described by Equations 1 and 2; it may include a cycle. Note also that tex2html_wrap_inline791 is the greatest lower bound of all sub-sequential limits of tex2html_wrap_inline793 as tex2html_wrap_inline795 approaches tex2html_wrap_inline797 .

 

 

The driving process is indicated by tex2html_wrap_inline799 . tex2html_wrap_inline801 is the total accumulated error in the virtual message output by the tex2html_wrap_inline787 LP from the driving process. tex2html_wrap_inline805 is the accumulated error in tex2html_wrap_inline797 actual time units from generation of the virtual message from the driving process. For example, if a prediction result is generated in the third LP from the driving process, then the total accumulated error in the result is tex2html_wrap_inline809 . If 10 represents the number of time units after the initial message was generated from the driving process then tex2html_wrap_inline811 would be the amount of total accumulated error in the result.


next up previous
Next: Optimum Choice of Verification Up: Characteristics of the Predictive Previous: Characteristics of the Predictive

Steve Bush
Thu Feb 27 15:34:42 CST 1997