Intelligent network manager for distributed multimedia conferencing
Mohammad Ahmad Al-Jarrah · OhioLink ETD Center (Ohio Library and Information Network) · 2000
In this dissertation, we study the problem of effective traffic management in the heavily loaded networks for videoconferencing from the real-time stochastic system perspective.A probabilistic delay model is proposed for the characterization of time-varying nature of the data traffic in the Internet.Connectionist delay representation of the network traffic is derived by considering a videoconference session among a group ofN participants connected via the Internet.Connections among the collaborative participants are represented by their end-to-end network delays statistics involving the characteristics of end-to-end transmission delay of each connection and the inter-connection relation.The first component is represented by the probability density function of the end-to-end delay in each connection.The second component is modeled as the delay correlation between the connections.For a network of N workstations, this model becomes an NxN matrix of probability density functions and N 2 x N 2 correlation matrix that, when normalized by the delay mean and variances of individual connections, leads to matrix of delay crosscorrelation coefficients with values varying in the range of [-1, 1] independent of scale changes in the correlation amplitude.For two connections, the higher the value of the cross-correlation coefficient the stronger the correlation between them is.This also means that two connections are sharing a portion of the Internet for their own communications.The shared portion of the network is XlFigure 5.25.The frame rate of the video signal displayed at packers' from bobcat in the third experiment ., ... ... ... ... ..