Nonlinear analysis of wireless LAN traffic

An understanding of traffic characteristics and accurate traffic models are necessary for the improvement of the capability of wireless networks. In this paper we have analyzed the nonlinear dynamical behavior of several real traffic traces collected from wireless testbeds. We have found strong evidence that the wireless traffic is chaotic from our observations. That is, we found from the correlation dimension, the largest Lyapunov exponent and the principal components for analysis, which are typical indicators of chaotic traffic. This gives us a good theoretical basis for the analysis and modeling of wireless traffic using chaos theory.