A Model for Traffic Prediction in Wireless Ad-Hoc Networks

In recent years, Wireless Ad-hoc networks have been considered as one of the most important technologies. The application domains of Wireless Ad-hoc Networks gain more and more importance in many areas. One of them is controlling and management the packet traffic. In this paper our goal is controlling the performance of every sections of pipeline of the factory by checking network periodically. Along the factory the traffic is modeled with a Poisson process. We present, with obtaining traffic packets at time (t) for each node in Wireless Ad-hoc Network, we can completely train a Neural Network and successfully predict the traffic at time (t+1) for each node. By this way we can recognize the inefficient sections in factory and try to fix it. The results of experiment have shown that proposed model has acceptable performance.