Network traffic prediction based on Hadoop

With the growing popularity of smart phones and the rapid development of Internet, the traditional network management system cannot adapt itself to the requirement intelligently. If we can use historic data to predict the trend of network traffic accurately, a better planning of network is more likely to be made and limited resource can be allocated and scheduled reasonably. However, massive amounts of data collected by network operators cannot be effectively processed. Therefore, in this paper, we design a network traffic prediction system based on Hadoop platform to process the real mobile network traffic data for a major network operator in China. With the Echo State Network (ESN), a new kind of Recurrent Neural Network (RNN) structure, the system can make accurate predictions of traffic variation trend for various network applications.