served from Figure 8.16 that the obtained overbooking factors are larger than 1. That means the proposed dimensioning approach is capable of attaining overbooking on the backbone link. Figure 8.16 also shows that the overbooking factors derived from the analytical approach comply with the simulations. From the presented results, the following conclusions can be drawn. From the presented dimensioning results for the last mile link and the backbone link as shown in Figure 8.14 and Figure 8.15, it is seen that the analytical dimensioning results match well with the simulation results. Thus it can be demonstrated that the proposed processor sharing model that is 8 Dimensioning for Multi-lub RAN Scenario extended for DiffServ for a single link (presented in section 7.3.1) can be applied well for dimensioning the individual links for elastic traffic in a star-structured multi-lub IP RAN. As it can provide sufficiently accurate estimations for the required bandwidth for each link. From Table 8.5, it is observed that for each QoS scenario using the obtained dimensioning results from simulations, the resultant QoS performance of each service class meets the individual defined delay requirement. It proves that the proposed dimensioning approach is able to guarantee the QoS of every service class in the DiffServ scenario for different QoS conditions. Furthermore, from Figure 8.16 it can be clearly seen that the proposed dimensioning approach is capable of attaining an optimistic overbooking on the backbone link. Overbooking factor for the backbone link Relative error of overbooking factor M/G/R/N-PS Simulation Target end-to-end delay factor Target end-to-end delay factor (a) overbooking factor (b) relative error Figure 8.16: Overbooking factor over different target delay factors in the star-structured IP- based UTRAN with DiffServ QoS scheme 8.4.3 Summary Section 8.4 discussed the dimensioning for elastic traffic in an IP based multi-lub radio access network, where the IP DiffServ QoS scheme is deployed individually at each