No abstract

We describe an approach and our experiences in applying federated simulation techniques to create large-scale parallel simulations of computer networks. Using the federated approach, the topology and the protocol stack of the simulated network is partitioned into a number of submodels, and a simulation process is instantiated for each one. Runtime infrastructure software provides services for interprocess communication and synchronization (time management). We first describe issues that arise in homogeneous federations where a sequential simulator is federated with itself to realize a parallel implementation. We then describe additional issues that must be addressed in heterogeneous federations composed of different network simulation packages, and describe a dynamic simulation backplane mechanism that facilitates interoperability among different network simulators. Specifically, the dynamic simulation backplane provides a means of addressing key issues that arise in federating different network simulators: differing packet representations, incomplete implementations of network protocol models, and differing levels of detail among the simulation processes. We discuss two different methods for using the backplane for interactions between heterogeneous simulators: the cross-protocol stack method and the split-protocol stack method. Finally, results from an experimental study are presented for both the homogeneous and heterogeneous cases that provide evidence of the scalability of our federated approach on two moderately sized computing clusters. Two different homogeneous implementations are described: Parallel/Distributed ns (pdns) and the Georgia Tech Network Simulator (GTNetS). Results of a heterogeneous implementation federating ns with GloMoSim are described. This research demonstrates that federated simulations are a viable approach to realizing efficient parallel network simulation tools.

Parallel discrete event simulation techniques have enabled the realization of large-scale models of communication networks containing millions of end hosts and routers. However, the performance of these parallel simulators could be severely degraded if proper synchronization algorithms are not utilized. In this paper, we compare the performance and scalability of synchronous and asynchronous algorithms for conservative parallel network simulation. We develop an analytical model to evaluate the efficiency and scalability of certain variations of the well-known null message algorithm, and present experimental data to verify the accuracy of this model. This analysis and initial performance measurements on parallel machines containing hundreds of processors suggest that for scenarios simulating scaled network models with constant number of input and output channels per logical process, an optimized null message algorithm offers better scalability than efficient global reduction based synchronous protocols.

No abstract

No abstract