In this paper, we compare the design and implementation of
a parallel simulation of a traffic flow network using two different
approaches: event-driven and time-driven. We begin by designing an
efficient event-driven approach to model the traffic network; our
design matches a time-driven model of the same traffic network. Our
experiments with the sequential implementation of the two approaches
correlates with previous research. Exploiting the look-ahead in the
event-driven model, we design a conservative parallel implementation
of the traffic flow problem where we obtain a maximum speedup of 9.27
using 16 Sun workstations. This speedup is appreciable since our parallel
architecture is parallel virtual machine (PVM), not known for fast
communication, and we use wall-clock time as a measure of execution speed.
We show that appreciable speedup can be achieved in parallelizing either
the event-driven or time-driven approach. We also show that speedup is
a misleading metric when used to compare the parallelizability of the
two approaches. Parallel performance, as measured by speedup, may be
better when the sequential performance is poor. For example, the
time-driven implementation achieved better speedup (3.21 to 3.56) than
the event-driven implementation (0.59 to 0.97) for few cars in the system;
however the sequential time-driven implementation required longer to
execute than the event-driven implementation for few cars in the system.
Similarly, for many cars in the system, the event-driven implementation
achieved better speedup (9.01 to 9.27) than the time-driven
implementation (5.99 to 9.12).