Mobility prediction in mobile ad-hoc network using deep learning

Nowadays, ad-hoc network becomes common to predict highly moveable devices. Deep learning is a proposed technique to predict based on the node movement history to know mobile stations current mobility information based on pause time, speed and movement direction. We used random waypoint mobility (RWM) principle to create location pattern for the proposed system. The simulation result shows that the proposed system can successfully predict the mobile user's mobility through RSS values in the dynamic environments.