Neural network-based load prediction for highly dynamic distributed online games

Abstract

We propose a neural network-based prediction method for the future entity layout in massively multiplayer online games. Our service has the potential to timely foresee critical hot-spots in fast-paced First Person Shooter action games that saturate the game servers which no longer respond to user actions at the required rate. Using our service, proactive load balancing (and redistribution) actions can be triggered. We show results based on a realistic simulation environment that demonstrate the advantages of our method compared to other conventional ones, especially due to its ability to adapt to different load patterns. © 2008 Springer-Verlag Berlin Heidelberg.