Abstract
Large-scale individual-based simulations can benefit a lot from high performance computing environments. The benefit that can be hopped for depends greatly on a good load distribution among the processing resources together with the minimization of the communication overhead. However, minimizing both idle time and communication overhead requires the search for a trade-off.
Inspired by complex systems, the approach described in this paper aims at minimizing the volume of data exchanged over the network between tasks of a distributed application, while balancing the load between available computing ressources. The method lies on the trail-laying trail-following paradigm used in algorithms based on artificial ants.