This paper presents an analytical model to evaluate the performance of parallel simulation on distributed computing platforms. The proposed model is formalized by two important time components in parallel and distributed processing: computation time and communication time. A conservative parallel simulation of multistage interconnection networks is used as an example in our analytical model. Performance metrics such as elapsed time, speedup and simulation bandwidth associated with different schemes for partitioning/mapping parallel simulation onto distributed processors are evaluated. Our mathematical analysis identifies the major constituents of simulation overheads in these mapping strategies necessary for improving parallel simulation efficiency. We also show that a perfectly balanced workload distribution may not necessarily translate into better performance. On the contrary, we have shown that a balanced mapping of workload may increase communication overheads resulting in a longer simulation elapsed time. Our performance model has been validated against implementation results from a parallel simulation model. The analytical framework is also practical to evaluate the runtime efficiency of other simulation applications which are based on the conservative paradigm.