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Abstract

An important issue for agent-based simulation architectures concerns the means by which agents can be kept up to date regarding the position and state of other agents and objects in their local environment. We implement two distributed publish-subscribe approaches and assess their performance within the SASSY architecture. The environment is decomposed into a set of regions, where an LP referred to as an Interest Manager (IM) manages each region. Publish-subscribe approaches have been utilized in other simulation environments (e.g., HLA), but we believe our approach is the first to use a peer-to-peer method in an optimistic environment. We assess the efficiency and scalability of these two methods by measuring the number of rollbacks and total runtime for various configurations of the simulation. Further, we evaluate the impact of varying the disparity of between the sensor and actuator regions.

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