Prediction model of mobility in MANET based on extreme learning machines
Qingli Zhang · Computer Engineering and Applications Journal · 2014
For the importance of mobile ad hoc networks(MANET)in managing resource availability of wireless network, a prediction model of mobility in MANET based on Extreme Learning Machines(ELM)is proposed to program availability of continuous service and effective energy management so as to improve total quality of service of network.ELM is used to model and predict mobility of arbitrary nodes in MANET. Each mobile node is assumed to know its current mobility information(position, speed and movement direction angle), and future node positions are predicted along with future distances between neighboring nodes. More realistic and accurate mobility prediction is generated based on several standard mobility models so as to capture better the existing interaction/correlation between cartesian coordinates of arbitrary nodes. The effectiveness of proposed model has been verified by simulation using standard mobility models illustrate. Simulation results show that proposed prediction model has improved over conventional model based on multilayer perception. It circumvents the prediction accuracy limitations in current algorithms when predicting future distances between neighboring nodes.