Self-Adaptive Dynamic Load Balancing for Large-Scale HLA-Based Simulations

Large-scale HLA-based simulations are susceptible to performance issues caused by load imbalances. High Level Architecture (HLA) was designed to organize distributed simulations, but it does not provide any mechanism to prevent imbalances. Also, several load balancing schemes have been proposed to properly re-arrange simulation load, but they do not present all the features needed for large-scale environments. A hierarchical, distributed balancing scheme has been designed to support the execution of such simulations, however, due to the balancing inter-relations, heterogeneity of resources, and cyclic load changes, the scheme reacts unnecessarily. Thus, a self-adaptive balancing scheme is proposed in order to dynamically re-configure the redistribution scheme and avoid the ones that are needless. Experimental results showed that the adaption technique improved the balancing efficiency since less migrations were required to achieve similar or better performance.