In previous work we presented the DTRD algorithm, an optimistic synchronisation algorithm for parallel discrete event simulation of multi-agent systems, and showed that it outperforms Time Warp and time windows on range of test cases. DTRD uses a decision theoretic model of rollback to derive an optimal time to delay read event so as to maximise the rate of LVT progression. The algorithm assumes that the inter-arrival times (both virtual and real) of events are normally distributed. In this paper we present a more detailed evaluation of the DTRD algorithm, and specifically how the performance of the algorithm is affected when the inter-arrival times do not follow the assumed distributions. Our analysis suggests that the performance of the algorithm is relatively insensitive to events whose inter-arrival times are not normally distributed. However as the variance of the input events increases its performance degrades to that of Time Warp. Our approach to evaluation is general, and we outline how the analysis may be applied to other decision theoretic algorithms.
['Michael Lees', 'Brian Logan', 'Dan Chen', 'Ton Oguara', 'Georgios K. Theodoropoulos']
Analysing Probabilistically Constrained Optimism