Parallel discrete-event simulation of FCFS stochastic queueing networks
PPEALS '88 Proceedings of the ACM/SIGPLAN conference on Parallel programming: experience with applications, languages and systems
Lightweight causal and atomic group multicast
ACM Transactions on Computer Systems (TOCS)
Exploiting temporal uncertainty in parallel and distributed simulations
PADS '99 Proceedings of the thirteenth workshop on Parallel and distributed simulation
Maintaining knowledge about temporal intervals
Communications of the ACM
The time and state relationships in simulation modeling
Communications of the ACM - Special issue on simulation modeling and statistical computing
Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
Interval Approximations of Message Causality in Distributed Executions
STACS '92 Proceedings of the 9th Annual Symposium on Theoretical Aspects of Computer Science
Space uncertain simulation events: some concepts and an application to optimistic synchronization
Proceedings of the eighteenth workshop on Parallel and distributed simulation
Exploiting Temporal Uncertainty in the Distributed Simulation of Time Petri Nets
ANSS '05 Proceedings of the 38th annual Symposium on Simulation
Bias in parallel and distributed simulation systems
WSC '05 Proceedings of the 37th conference on Winter simulation
On Parallel Stochastic Simulation of Diffusive Systems
CMSB '08 Proceedings of the 6th International Conference on Computational Methods in Systems Biology
Controlling Bias in Optimistic Simulations with Space Uncertain Events
DS-RT '08 Proceedings of the 2008 12th IEEE/ACM International Symposium on Distributed Simulation and Real-Time Applications
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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In this paper we describe an approach to exploit temporal uncertainty in parallel and distributed simulation by utilizing time intervals rather than precise time stamps. Unlike previously published work that propose new message ordering semantics, our approach is based on conservative, time stamp order execution and enhancing the lookahead of the simulation by pre-drawing random numbers from a distribution that models temporal uncertainty. The advantages of this approach are that it allows time intervals to be exploited using a conventional Time Stamp Order (TSO) delivery mechanism, and it offers the modeler greater statistical control over the assigned time stamps. An implementation of this approach is described and initial performance measurements are presented.