  This paper is about partitioning in parallel and distributed simulation. That
means decomposing the simulation model into a numberof components and to
properly allocate them on the execution units. An adaptive solution based on
self-clustering, that considers both communication reduction and computational
load-balancing, is proposed. The implementation of the proposed mechanism is
tested using a simulation model that is challenging both in terms of structure
and dynamicity. Various configurations of the simulation model and the
execution environment have been considered. The obtained performance results
are analyzed using a reference cost model. The results demonstrate that the
proposed approach is promising and that it can reduce the simulation execution
time in both parallel and distributed architectures.
