A migration based middleware can adaptively optimize the simulation execution by reallocating the simulated entities over the distributed simulation. The dynamic reallocation can reduce the communication overhead and improves the computation load balancing. This translates into a reduction of the Wall-Clock Time (WCT) needed to complete the parallel and distributed simulation runs.

The Generic Adaptive Interaction Architecture (GAIA) is a migration based framework integrated in ARTÌS. The basic task of GAIA is to check the communication pattern of each simulated entity during all the simulation execution. A set of heuristics evaluates the communication pattern and trigger the entities reallocation to reduce the communication costs and to improve the load balancing of the execution architecture [MSWIM2004] . GAIA clusters the highly interacting simulated entities within the same execution unit, reducing costly network communication and increasing the rate of low cost local communication [DSRT2004] .

An enhanced version of the GAIA framework (called GAIA+) has been designed and implemented to support the distributed simulation over shared Commercial Off-the-Shelf (COTS) clusters and to enhance the load balancing and communication overheads’ reduction in presence of massive models of dynamically interacting simulated entities, heterogeneous execution architectures and unpredictable computation and communication (background) loads. The adaptive load balancing mechanisms could improve the resources utilization and the simulation process execution, by dynamically tuning the simulation load, taking care of the synchronization and communication overheads reduction. One of the main goals of GAIA+ is to enhance the simulation execution on clusters with heterogeneous units connected by a computer network. Heterogeneity is intended here in terms of CPU's performance characteristics, available resources, and background load.

• More in deep information about GAIA and GAIA+ can be found in IJSPM09.
• For more information on the ARTÌS installation and usage please see the ARTÌS & GAIA HOWTO.
• Some videos that show how GAIA works can be found in this page.

We are currently working on an extended version of GAIA (called ReliableGAIA, R-GAIA) that aims to introduce some fault-tolerance to the simulation execution. This will permit to run simulations on top of unreliable execution platforms such as the public cloud. For more information please see HPCS11. Furthermore, in the PArallel Graph Algorithms (PAGA) research project we are working on the porting of ARTÌS/GAIA to the Blue Gene/Q architecture.