.(f1,f2) f=f1+f2-1 =f1+f2-1 simulation Last mile utilization last mile utilization Figure 8.7: Delay estimations for case (3): congested backbone and last mile links 8.3.2 Dimensioning Approaches Based on the above proposed application performance estimation methods, this section is going to propose several dimensioning approaches for a star-structured multi-lub RAN determine the suitable bandwidth for the last mile link and the backbone link separately. The objective of dimensioning is to guarantee a certain average transfer time T for a file of size Xt or average throughput D on an end-to-end basis with the minimum network costs. Equivalently, dimensioning can be driven by satisfying an end-to-end delay factor f which results in the desired average transfer time T (T = Tmin f f or the average throughput Dt (Dt = peak! f) for all file transactions. In this context, the task of dimensioning of a star-structured multi-lub RAN is to distribute the total allowed congestion (represented by the end-to-end delay factor f) on the individual links over the transport path, i.e. to assign proper target delay factors for the last mile link and the backbone link individually to achieve the desired end-to- end delay factor f The assignment of a proper target delay factor for each link needs consider the impact of each link on the end-to-end application QoS and its resultant transport costs. Let a target end-to-end delay factor frarget represent the required application QoS level for a specific service class on all lub interfaces. Depending on the value of flarget , three basic approaches are proposed in this thesis to assign the separate target delay factor for the last mile link and the backbone link individually: (1) If the desired end-to-end delay factor flarget is close to 1, which is a practical case for network dimensioning, each link can be dimensioned according to flarget That means, the assigned delay factor for the last mile link and the backbone are set to the same delay factor equal to frarget i.e. = = As the desi