Discrete event simulations and parallel processing: statistical properties
SIAM Journal on Scientific and Statistical Computing
Unboundedly parallel simulations via recurrence relations
SIGMETRICS '90 Proceedings of the 1990 ACM SIGMETRICS conference on Measurement and modeling of computer systems
A time-division algorithm for parallel simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Time-segmentation parallel simulation of networks of queues with loss or communication blocking
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Parallel and distributed discrete event simulation: algorithms and applications
WSC '93 Proceedings of the 25th conference on Winter simulation
Proceedings of the 29th conference on Winter simulation
Parallel trace-driven cache simulation by time partitioning
WSC' 90 Proceedings of the 22nd conference on Winter simulation
Parallel simulation by multi-instruction, longest-path algorithms
Queueing Systems: Theory and Applications
Parallel simulation of queueing networks by time segmentation
Parallel simulation of queueing networks by time segmentation
Proceedings of the 29th conference on Winter simulation
Time segmentation parallel simulation of tandem queues with manufacturing blocking
Proceedings of the 30th conference on Winter simulation
Challenges and benefits of time-parallel simulation of wireless ad hoc networks
valuetools '06 Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
Time-parallel simulation of wireless ad hoc networks with compressed history
Journal of Parallel and Distributed Computing
Time-parallel simulation of wireless ad hoc networks
Wireless Networks
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In this paper we present a time parallel simulation approach and discuss conditions under which this approach is applicable. Our approach involves distributing the available processors among segments of the time horizon of the simulation. We show that under certain conditions, sample paths of the system generated by a common sequence of potential events will couple (i.e., become identical) with probability one. This property will be exploited to efficiently combine the information collected on different segments of the sample path and generate a complete valid sample path. We show that the expected coupling time of the system (i.e., the amount of time required for all the sample paths of the system to couple) is essential to the efficiency of the approach. We apply our parallel simulation approach to a class of Markovian queueing networks and investigate the efficiency of the method by providing bounds and estimates for the expected coupling times.