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

A brief simulation study of real-time packet-dispersion mode-tracking using the Gaussian-Mix Model (originally devised for real-time background classification in moving pictures) and an adaptation of the Kernel-Density Estimator is presented. The simulated environment consisted of two FIFO store-and-forward nodes where the probe packets interact with Poisson and Pareto-generated cross-traffic with a range of packet sizes. The two models produced broad v similar results, able to track node activity under the dynamically changing conditions associated with the Pareto cross-traffic. The Gaussian model sometimes replaced the primary mode with a double peak, which disappeared when some of the model's parameters were changed.