The threshold of event simultaneity
Proceedings of the eleventh workshop on Parallel and distributed simulation
On event ordering in parallel discrete event simulation
PADS '99 Proceedings of the thirteenth workshop on Parallel and distributed simulation
Simultaneous events and distributed simulation
WSC' 90 Proceedings of the 22nd conference on Winter simulation
Simultaneous events and lookahead in simulation protocols
ACM Transactions on Modeling and Computer Simulation (TOMACS)
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Parallel and Distribution Simulation Systems
Parallel and Distribution Simulation Systems
Sequential Performance of Asynchronous Conservative PDES Algorithms
Proceedings of the 19th Workshop on Principles of Advanced and Distributed Simulation
Algorithms for HLA-based distributed simulation cloning
ACM Transactions on Modeling and Computer Simulation (TOMACS)
COTS Simulation Package (CSP) Interoperability -A Solution to Synchronous Entity Passing
Proceedings of the 20th Workshop on Principles of Advanced and Distributed Simulation
Channel based sequential simulation
WSC '05 Proceedings of the 37th conference on Winter simulation
Inside discrete-event simulation software: how it works and why it matters
Proceedings of the 38th conference on Winter simulation
A Flexible Dynamic Partitioning Algorithm for Optimistic Distributed Simulation
Proceedings of the 21st International Workshop on Principles of Advanced and Distributed Simulation
Efficient Analysis of Simultaneous Events in Distributed Simulation
DS-RT '07 Proceedings of the 11th IEEE International Symposium on Distributed Simulation and Real-Time Applications
HPCC'05 Proceedings of the First international conference on High Performance Computing and Communications
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Discrete-event simulation is a very popular technique for the performance evaluation of systems, and in widespread use in network simulation tools. It is well known, however, that discrete-event simulation suffers from the problem of simultaneous events: Different execution orders of events with identical timestamps may lead to different simulation results. Current simulation tools apply tie-breaking mechanisms which order simultaneous events for execution. While this is an accepted solution, a legitimate question is: Why should only a single simulation result be selected, and other possible results be ignored? In this paper, we argue that confidence in simulation results may be increased by analyzing the impact of simultaneous events. We present a branching mechanism which examines different execution orders of simultaneous events, and may be used in conjunction with, or as an alternative to tie-breaking rules. We have developed a new simulation tool, MOOSE, which provides branching mechanisms for both sequential and distributed discrete-event simulation. While MOOSE has originally been developed for network simulation, it is fully usable as a general simulation tool.