ue to a higher priority. Thus, the following analytical calculations are focused on estimating the queuing delay distribution of the low priority traffic. In [HZ05], the Laplace-Stieltjes 6.4 Dimensioning for Transport Network Performance transform (LST) of the delay distribution of a low priority packet in an MMPP/G/1 non- preemptive queue is given as follows: (6.57) The mean sojourn time for the low priority packet is [HZ05]: (6.58) M*(s) is the LST of the high priority busy period distribution, which is calculated as [*(s)=B*[s-(M*(s)-1)2] (6.59) However, the cumulative delay distribution function (i.e. CDF) for low priority packets W(x) is difficult to obtain by implementing the inverse Laplace transform for equation (6.57). Therefore it is proposed in this thesis to approximate it with a two-term exponential function: (6.60) The asymptotic decay rate S1 and S2 can be derived from the first and second moment of the delay distribution for a low priority packet. 6.4.3.4 Iub Dimensioning with MMPP As introduced in section 6.4.3.1, a two-state MMPP model is characterized by four parameters: A1, A2, r1 and r2. AI denotes the mean arrival rate of source 1 and A2 is the mean arrival rate of source 2. 1/r1 is the mean holding period of the source 1 and 1/r2 is the mean holding period of the source 2. The setting of these four MMPP parameters is based on certain MMPP fitting methods. The fitting method used in this thesis is the interarrival time distribution inference procedure [NSV99]. In this approach, the four MMPP parameters are estimated based on the Cumulative Distribution Functions (CDF) of the interarrival time distributions. The interarrival time distributions for the AAL2 packets can be based on a 2- Phase Hyper-exponential distribution, denoted as Hyper (2), which is described by the following three parameters: a - the mean arrival rate of flow 1; a2 - the mean arrival rate of flow 2; p1 - the probability of flow 1. The main reason of using a 2-Phase Hyper-exponential distribution for the interarrival time