ACM Transactions on Programming Languages and Systems (TOPLAS)
Numerical solution for the departure process from the Gl/G/1 queue
Computers and Operations Research
SPAA '89 Proceedings of the first annual ACM symposium on Parallel algorithms and architectures
Accounting for input model and parameter uncertainty in simulation
Proceedings of the 33nd conference on Winter simulation
Input uncertainty: accounting for parameter uncertainty in simulation input modeling
Proceedings of the 33nd conference on Winter simulation
Input modeling: input model uncertainty: why do we care and what should we do about it?
Proceedings of the 35th conference on Winter simulation: driving innovation
Ad Hoc Distributed Simulations
Proceedings of the 21st International Workshop on Principles of Advanced and Distributed Simulation
Reliable simulation with input uncertainties using an interval-based approach
Proceedings of the 40th Conference on Winter Simulation
Ad Hoc Distributed Simulation of Queueing Networks
PADS '10 Proceedings of the 2010 IEEE Workshop on Principles of Advanced and Distributed Simulation
A framework for input uncertainty analysis
Proceedings of the Winter Simulation Conference
Statistical issues in ad hoc distributed simulations
Proceedings of the Winter Simulation Conference
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Ad hoc distributed simulations are constructed by embedding online simulations into a network of sensors. Recent work examining the effectiveness of ad hoc distributed simulations in modeling open queueing networks has been limited to a specific network configuration. This paper examines the accuracy of the ad hoc approach more broadly for open queueing networks. First, we identify conditions where the ad hoc approach will yield accuracy comparable to traditional replicated simulations. For cases where these conditions do not apply, we propose a "buffered-area" mechanism to improve the accuracy of system performance estimates. Empirical evidence is presented showing that this mechanism helps achieve a substantial bias reduction with a moderate increase in execution time.