Exploiting Neuro-Fuzzy System for Mobility Prediction in Wireless Ad-Hoc Networks.

Ad-hoc mobile wireless network is characterized by a very dynamic environment. However, the major obstacle to be resolved is to sustain the links of continuity and improved routing performance. In this paper, we propose a predictor based Neuro-fuzzy for the prediction of mobility. It predicts the trajectory of an ad-hoc mobile node in order to improve routing performance by reducing overhead and the number of broken connections. It allows estimating the stability of paths in Ad-Hoc mobile wireless networks. Using an Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict the trajectory of an ad-hoc mobile, we demonstrate the effectiveness of the proposed predictor by testing it on a time series prediction problems.