A Federated Approach to Distributed Network Simulation

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.

Publication
ACM Transactions on Modeling and Computer Simulation (TOMACS) (Vol. 14, No. 2)

[Pub 12]

Kalyan Perumalla
Kalyan Perumalla

As a Federal Program Manager in Advanced Scientific Computing Research at the U.S. Dept. of Energy, Office of Science, Kalyan Perumalla manages a $100-million R&D portfolio covering AI, HPC, Quantum, SciDAC, and Basic Computer Science. In his 25-year R&D leadership experience, he previously led advanced R&D as Distinguished Research Staff Member at the Oak Ridge National Laboratory (ORNL) developing scalable software and applications on the world’s largest supercomputers for 17 years, including as a line manager and a founding group leader. He has held senior faculty and adjunct appointments at UTK, GT, and UNL, and was an IAS Fellow at Durham University.

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