VR traffic Prediction from head movement Data

The objective of this research is to determine whether features extracted from head movement data can effectively predict periods of high and low network demand. This investigation examines whether such predictive capabilities could enable dynamic resource allocation strategies that maintain optimal network performance while minimizing latency. The study also explores the impact of different game dynamics on traffic patterns, aiming to establish whether game-specific factors influence the predictability of network demand. Through this research, we seek to contribute valuable insights into the potential of using user behavior data for enhancing network management in VR environments.