The performance of distributed simulation depends very much on the partitioning of the simulation model among the participating hosts. Usually, when starting a simulation run, an initial partitioning is determined by taking into account the available computing resources as well as the expected workload and the communication structure of the simulation model. However, as hosts can be subject to background load or the model behavior can change in the course of the simulation, a dynamic partitioning mechanism is required to avoid inefficiencies.

In this paper, we introduce a new dynamic partitioning algorithm for optimistic distributed simulation. The algorithm is generally applicable but can also be configured to meet the requirements of specific scenarios. It is based on performance estimates for both computation and communication workload, the calculation of which is completely platform-independent. Our experiments show that the algorithm has low overhead and reacts reliably to changes of both model behavior and external resources.