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