Design And Implementation Of The LTE Network Traffic Generator Based On Network Flow Engine Card

The real network traffic is the basis for studying these problems, such as trafficmanagement, security monitoring, and guarantee for quality of service. The diversification ofnetwork services results in that the network traffic characteristics are increasingly complex.Therefore, the research on a traffic generator which has the traffic characteristics of thenext-generation Long Term Evolution (LTE) network is of importance.Supported by the National High-Tech Development Project (863project), the test andsimulation of next generation converged satellite and terrestrial broadband communicationnetworks, this dissertation has mainly performed the design and implementation of a trafficgenerator, which could be used in LTE network and is based on NFE3240network flowengine card. Firstly, this dissertation introduces the characteristics and models of networktraffic. By comparing several current network traffic models, we propose a self-similarsequence generation scheme known as MWM+FGN which adopts the Multi-fractal WaveletModel (MWM) to improve the Fractional Gaussian Noise (FGN) process, thus implementingthe self-similar network traffic generation. The NFE3240is chosen as the hardware platformby comparing and analyzing the current development platforms of network traffic generators.According to the proposed scheme for generating the self-similar sequence and itsimplementation procedure, this dissertation has completed the overall design andimplementation of a traffic generator. Finally, we inspect the only self-similar criteria of Hparameter by using the method of Rescaled Range analysis (R/S), and the result shows thatthe scheme proposed in this dissertation improves the relative error ratio of H parameter insome extent.Also, the application of a traffic generator in LTE networks is presented.