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PREDICTIVE ALGORITHMS FOR AGGREGATION AND DISAGGREGATION IN MIXED MODE SIMULATION

By Benjamin Yuan, Wei Chua, Malcolm Yoke and Hean Low

Abstract

One of the issues in mixed mode simulation is the need to achieve a believable and valid state of interoperability within the simulation itself. This is achieved in part through aggregation/disaggregation, Multi Resolution Entities or other methods, which deal with the interoperability and believability issues with different amounts of success. These approaches can be improved with the inclusion of predictive algorithms that can reduce the amount of aggregation/disaggregation in dense or thrashing scenarios. In this paper, we discuss the issues of consistency in mixed mode simulation in the context of the High Level Architecture and proposed a set of predictive algorithms to improve its efficiency. We carried out a set of experiments using these algorithms in a mixed mode simulation to assess their effects on consistency and efficiency. The experimental results show that the algorithms can improve the simulation performance by reducing the amount of aggregation/disaggregation in dense interaction scenarios.

Year: 2012
OAI identifier: oai:CiteSeerX.psu:10.1.1.211.5297
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