Prediction-based location management using multilayer neural networks

Location management is one of the key issues in mobile networks to provide an efficient and low-cost services. In this paper, we propose a prediction-based location management scheme for locating a mobile host (MH), which depends on its history of movement pattern. A multilayer neural network (MNN) model for mobile movement prediction is designed to predict the future movement of a mobile host. The MNNs are trained with respect to the data obtained from the movement pattern of a mobile host for making predictions. The performance of the method has been verified for prediction accuracy by considering different movement patterns of a mobile host. The simulation has achieved an average of 93% prediction accuracy for uniform movement, 40% to 70% for regular movement and 2% to 30% for random movement patterns of an MH.