An Online Influence Detection Algorithm for Organic Computing Systems

In recent years, technical systems have become substantially more complex due to an increasing number of subsystems, the interactions between them, and the mutual influence on each other. Often, even today's systems are no longer manageable by humans and this trend is assumed to intensify rapidly. Therefore, the Organic Computing initiative develops techniques in order to put these systems on a self-organized and self-adaptive level. In this work, we provide a novel method for the detection of mutual influences in Organic Computing systems through the adaption of stochastic dependency measures. We depict how the quantification and detection of such influences take place and verify the appropriate function through simulations of a typical Organic Computing system.