Performance of Voice/Data Integration on a TDM System

Data queueing is of primary concern in a voice/data integrated TDM system. The data queueing model is represented in the discrete-time domain with multiple servers and voice is given a higher priority than data. The data arrival process is assumed to be Poisson and the voice arrival process is characterized by a Markov chain. The correlation coefficient of the number of on voice calls between consecutive frames is used to measure the correlation behavior of the voice process. While the generating function approach may be used to analyze the queueing process, it involves the evaluation of a large number of boundary terms. On the assumption that the voice traffic consists of i.i.d. two-state Markov chains, we derive a simple expression for the mean queue size as a function of two variables in the form of the traffic departure processes. The results clearly reveal a significant influence of the correlation coefficient on the data queueing process. Then, an approximate analysis based on the departure processes is introduced. The numerical and simulation results indicate that this approximate approach yields reasonably accurate results.