Real-Time Tracking of Packet-Pair Dispersion Nodes Using the Kernel-Density and Gaussian-Mixture Models

A brief simulation study of real-time packetdispersionmode-tracking using the Gaussian-MixModel (originally devised for real-time backgroundclassification in moving pictures) and an adaptationof the Kernel-Density Estimator is presented. Thesimulated environment consisted of two FIFO storeand-forward nodes where the probe packets interactwith Poisson and Pareto-generated cross-trafficwith a range of packet sizes. The two modelsproduced broadly similar results, able to track nodeactivity under the dynamically changing conditionsassociated with the Pareto cross-traffic. TheGaussian model sometimes replaced the primarymode with a double peak, which disappeared whensome of the model’s parameters were changed.

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