Evolutionary optimization of parameters for distributed virtual environments

In a distributed virtual environment interest management schemes attempt to ensure virtual world objects exchange messages only if they are interacting. This provides an opportunity to allow such systems to scale to support many hundreds, even thousands, of virtual world objects by reducing the need to send and process unnecessary messages. However, arriving at the optimum configuration for the interest management scheme is a challenging and complex problem. The customary approach is to configure parameters in an ad-hoc manner (supported by experience). However, such an approach is unlikely to yield optimum system performance. Here we propose a means of finding optimal parameter values by way of a simulation tool equipped with evolutionary optimization capabilities. We provide a series of experiments that indicate that our simulator can aid in configuring interest management schemes to gain better system performance.