Basics of Computer Network Simulation

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Basics of  Computer Network Simulation

                        A simulation is, more or less, a combination of art and science. That is, while
the expertise in computer programming and the applied mathematical tools
account for the science part, the very skill in analysis and conceptual model
formulation usually represents the art portion.
                        A long list of steps in executing
a simulation process, as given in [2], seems to reflect this popular claim.
Basically, all these steps can be put into three main tasks each of which carries
different degrees of importance.
                        According to Shannon [2], it is recommended that 40 percent of time and
effort be spent on defining a problem, designing a corresponding model, and
devising a set of experiments to be performed on the simulation model. Further,
it was pointed out that a portion of 20 percent should be used to program
the conceptual elements obtained during the first step.
                        Finally, the remaining
40 percent should be utilized in verifying/validating the simulation model, experimenting
with designed inputs (and possibly fine-tuning the experiments
themeselves), and analyzing the results.  
                       We note that this formula is in no
way a strict one. Any actual simulation may require more or less time and
effort, depending on the context of interest and, definitely, on the modeler
himself/herself.
                     A simulation can be thought of as a flow process of network entities (e.g.,
nodes, packets). As these entities move through the system, they interact with
other entities, join certain activities, trigger events, cause some changes to the
state of the system, and leave the process.
                  From time to time, they contend
or wait for some type of resources. This implies that there must be a logical
execution sequence to cause all these actions to happen in a comprehensible
and manageable way. An execution sequence plays an important role in
supervising a simulation and is sometimes used to characterize the types of
simulation.
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